diff --git a/compile-results.ipynb b/compile-results.ipynb
index 54949ef813039d3f0fc9b25b737f5b14cdabcd0d..6f55c1399c7e53e4cfe101722f5f82e69d8017dd 100644
--- a/compile-results.ipynb
+++ b/compile-results.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 85,
"metadata": {},
"outputs": [
{
@@ -11,10 +11,10 @@
"text": [
"Defaulting to user installation because normal site-packages is not writeable\n",
"Requirement already satisfied: pandas in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (2.2.0)\n",
+ "Requirement already satisfied: pytz>=2020.1 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2024.1)\n",
"Requirement already satisfied: python-dateutil>=2.8.2 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2.8.2)\n",
- "Requirement already satisfied: tzdata>=2022.7 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2024.1)\n",
"Requirement already satisfied: numpy<2,>=1.22.4 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (1.26.1)\n",
- "Requirement already satisfied: pytz>=2020.1 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2024.1)\n",
+ "Requirement already satisfied: tzdata>=2022.7 in /Users/picocreator/Library/Python/3.9/lib/python/site-packages (from pandas) (2024.1)\n",
"Requirement already satisfied: six>=1.5 in /Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/site-packages (from python-dateutil>=2.8.2->pandas) (1.15.0)\n",
"\u001b[33mWARNING: You are using pip version 21.2.4; however, version 24.0 is available.\n",
"You should consider upgrading via the '/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n"
@@ -36,14 +36,14 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 86,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Found 3025 results.json files\n"
+ "Found 3276 results.json files\n"
]
}
],
@@ -71,7 +71,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 87,
"metadata": {},
"outputs": [
{
@@ -156,16 +156,16 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 88,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Found 57 models\n",
+ "Found 64 models\n",
"Models: \n",
- "['mistralai/Mistral-7B-v0.1', 'mosaicml/mpt-7b-instruct', 'mosaicml/mpt-7b', 'mosaicml/mpt-7b-chat', 'bigscience/bloom-7b1', 'bigscience/bloomz-7b1-mt', 'bigscience/bloomz-7b1', 'EleutherAI/pythia-2.8b', 'EleutherAI/pythia-1.4b', 'EleutherAI/gpt-j-6b', 'EleutherAI/pythia-6.9b', 'google/flan-t5-base', 'google/gemma-2b', 'google/gemma-2b-it', 'google/gemma-7b', 'google/gemma-7b-it', 'google/flan-t5-large', 'microsoft/phi-1_5', 'microsoft/phi-2', 'microsoft/phi-1', 'allenai/OLMo-7B', 'TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T', 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', 'RWKV/rwkv-5-world-1b5', 'RWKV/rwkv-5-world-3b', 'RWKV/rwkv-4-world-3b', 'RWKV/rwkv-4-world-1b5', 'RWKV/v5-Eagle-7B-HF', 'RWKV/rwkv-4-world-7b', './rwkv-x-dev/chunk4-0_85_pth', './rwkv-x-dev/chunk1-0_8_pth', './rwkv-x-dev/chunk0-0_8_pth', './rwkv-x-dev/chunk2-0_8_pth', './rwkv-x-dev/chunk3-0_8_pth', './rwkv-x-dev/chunk7-2-0_85_pth', './rwkv-x-dev/chunk5-0_85_pth', './rwkv-x-dev/RWKV-5-World-1B5-v2-20231025-ctx4096', './rwkv-x-dev/chunk8-1-0_85_pth', './rwkv-x-dev/r3-c1-8_pth', './rwkv-x-dev/RWKV-5-World-3B-v2-20231118-ctx16k', './rwkv-x-dev/RWKV-5-World-7B-v2-20240128-ctx4096', './rwkv-x-dev/chunk6-0_85_pth', './rwkv-x-dev/chunk7-1-0_85_pth', './rwkv-x-dev/Hermes-RWKV-v5-7B_pth', 'togethercomputer/RedPajama-INCITE-7B-Base', 'togethercomputer/RedPajama-INCITE-7B-Instruct', 'togethercomputer/RedPajama-INCITE-7B-Chat', 'facebook/opt-2.7b', 'facebook/opt-6.7b', 'facebook/opt-1.3b', 'tiiuae/falcon-7b-instruct', 'tiiuae/falcon-rw-1b', 'tiiuae/falcon-rw-7b', 'tiiuae/falcon-7b', 'huggyllama/llama-7b', 'meta-llama/Llama-2-7b-chat-hf', 'meta-llama/Llama-2-7b-hf']\n",
+ "['mistralai/Mistral-7B-v0.1', 'mosaicml/mpt-7b-instruct', 'mosaicml/mpt-7b', 'mosaicml/mpt-7b-chat', 'bigscience/bloom-7b1', 'bigscience/bloomz-7b1-mt', 'bigscience/bloomz-7b1', 'EleutherAI/pythia-2.8b', 'EleutherAI/pythia-1.4b', 'EleutherAI/gpt-j-6b', 'EleutherAI/pythia-6.9b', 'google/flan-t5-base', 'google/gemma-2b', 'google/gemma-2b-it', 'google/gemma-7b', 'google/gemma-7b-it', 'google/flan-t5-large', 'microsoft/phi-1_5', 'microsoft/phi-2', 'microsoft/phi-1', 'allenai/OLMo-7B', 'TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T', 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', 'RWKV/rwkv-5-world-1b5', 'RWKV/rwkv-5-world-3b', 'RWKV/rwkv-4-world-3b', 'RWKV/rwkv-4-world-1b5', 'RWKV/v5-Eagle-7B-HF', 'RWKV/rwkv-4-world-7b', 'aisingapore/sealion7b', 'aisingapore/sealion3b', './rwkv-x-dev/chunk4-0_85_pth', './rwkv-x-dev/chunk1-0_8_pth', './rwkv-x-dev/chunk0-0_8_pth', './rwkv-x-dev/chunk2-0_8_pth', './rwkv-x-dev/chunk3-0_8_pth', './rwkv-x-dev/r3-testchunk-1-8_pth', './rwkv-x-dev/chunk7-2-0_85_pth', './rwkv-x-dev/r3-testchunk2-blink_pth', './rwkv-x-dev/chunk5-0_85_pth', './rwkv-x-dev/RWKV-5-World-1B5-v2-20231025-ctx4096', './rwkv-x-dev/chunk8-1-0_85_pth', './rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup_pth', './rwkv-x-dev/r3-c1-8_pth', './rwkv-x-dev/RWKV-5-World-3B-v2-20231118-ctx16k', './rwkv-x-dev/RWKV-5-World-7B-v2-20240128-ctx4096', './rwkv-x-dev/chunk6-0_85_pth', './rwkv-x-dev/chunk7-1-0_85_pth', './rwkv-x-dev/r3-testchunk2_pth', './rwkv-x-dev/Hermes-RWKV-v5-7B_pth', './rwkv-x-dev/r3-testchunk-blink_pth', 'togethercomputer/RedPajama-INCITE-7B-Base', 'togethercomputer/RedPajama-INCITE-7B-Instruct', 'togethercomputer/RedPajama-INCITE-7B-Chat', 'facebook/opt-2.7b', 'facebook/opt-6.7b', 'facebook/opt-1.3b', 'tiiuae/falcon-7b-instruct', 'tiiuae/falcon-rw-1b', 'tiiuae/falcon-rw-7b', 'tiiuae/falcon-7b', 'huggyllama/llama-7b', 'meta-llama/Llama-2-7b-chat-hf', 'meta-llama/Llama-2-7b-hf']\n",
"Saved to compiled-lm-eval-results.json\n"
]
}
@@ -199,7 +199,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 89,
"metadata": {},
"outputs": [
{
@@ -465,6 +465,22 @@
" \n",
"
\n",
" 29 | \n",
+ " aisingapore/sealion7b | \n",
+ " 0.559818 | \n",
+ " 0.060680 | \n",
+ " 0.559818 | \n",
+ " 0.060680 | \n",
+ "
\n",
+ " \n",
+ " 30 | \n",
+ " aisingapore/sealion3b | \n",
+ " 0.559273 | \n",
+ " 0.054490 | \n",
+ " 0.559273 | \n",
+ " 0.054490 | \n",
+ "
\n",
+ " \n",
+ " 31 | \n",
" togethercomputer/RedPajama-INCITE-7B-Base | \n",
" 0.525455 | \n",
" 0.036407 | \n",
@@ -472,7 +488,7 @@
" 0.036407 | \n",
"
\n",
" \n",
- " 30 | \n",
+ " 32 | \n",
" togethercomputer/RedPajama-INCITE-7B-Instruct | \n",
" 0.528545 | \n",
" 0.036470 | \n",
@@ -480,7 +496,7 @@
" 0.036470 | \n",
"
\n",
" \n",
- " 31 | \n",
+ " 33 | \n",
" togethercomputer/RedPajama-INCITE-7B-Chat | \n",
" 0.535455 | \n",
" 0.038723 | \n",
@@ -488,7 +504,7 @@
" 0.038723 | \n",
"
\n",
" \n",
- " 32 | \n",
+ " 34 | \n",
" facebook/opt-2.7b | \n",
" 0.521818 | \n",
" 0.029821 | \n",
@@ -496,7 +512,7 @@
" 0.029821 | \n",
"
\n",
" \n",
- " 33 | \n",
+ " 35 | \n",
" facebook/opt-6.7b | \n",
" 0.522909 | \n",
" 0.027216 | \n",
@@ -504,7 +520,7 @@
" 0.027216 | \n",
"
\n",
" \n",
- " 34 | \n",
+ " 36 | \n",
" facebook/opt-1.3b | \n",
" 0.521818 | \n",
" 0.029112 | \n",
@@ -512,7 +528,7 @@
" 0.029112 | \n",
"
\n",
" \n",
- " 35 | \n",
+ " 37 | \n",
" tiiuae/falcon-7b-instruct | \n",
" 0.536727 | \n",
" 0.053430 | \n",
@@ -520,7 +536,7 @@
" 0.053430 | \n",
"
\n",
" \n",
- " 36 | \n",
+ " 38 | \n",
" tiiuae/falcon-rw-1b | \n",
" 0.522545 | \n",
" 0.029446 | \n",
@@ -528,7 +544,7 @@
" 0.029446 | \n",
"
\n",
" \n",
- " 37 | \n",
+ " 39 | \n",
" tiiuae/falcon-rw-7b | \n",
" 0.535818 | \n",
" 0.033185 | \n",
@@ -536,7 +552,7 @@
" 0.033185 | \n",
"
\n",
" \n",
- " 38 | \n",
+ " 40 | \n",
" tiiuae/falcon-7b | \n",
" 0.559636 | \n",
" 0.071650 | \n",
@@ -544,7 +560,7 @@
" 0.071650 | \n",
"
\n",
" \n",
- " 39 | \n",
+ " 41 | \n",
" huggyllama/llama-7b | \n",
" 0.541818 | \n",
" 0.040718 | \n",
@@ -552,7 +568,7 @@
" 0.040718 | \n",
"
\n",
" \n",
- " 40 | \n",
+ " 42 | \n",
" meta-llama/Llama-2-7b-chat-hf | \n",
" 0.559818 | \n",
" 0.054954 | \n",
@@ -560,7 +576,7 @@
" 0.054954 | \n",
"
\n",
" \n",
- " 41 | \n",
+ " 43 | \n",
" meta-llama/Llama-2-7b-hf | \n",
" 0.566727 | \n",
" 0.052515 | \n",
@@ -602,19 +618,21 @@
"26 RWKV/rwkv-4-world-1b5 0.554000 \n",
"27 RWKV/v5-Eagle-7B-HF 0.622364 \n",
"28 RWKV/rwkv-4-world-7b 0.601455 \n",
- "29 togethercomputer/RedPajama-INCITE-7B-Base 0.525455 \n",
- "30 togethercomputer/RedPajama-INCITE-7B-Instruct 0.528545 \n",
- "31 togethercomputer/RedPajama-INCITE-7B-Chat 0.535455 \n",
- "32 facebook/opt-2.7b 0.521818 \n",
- "33 facebook/opt-6.7b 0.522909 \n",
- "34 facebook/opt-1.3b 0.521818 \n",
- "35 tiiuae/falcon-7b-instruct 0.536727 \n",
- "36 tiiuae/falcon-rw-1b 0.522545 \n",
- "37 tiiuae/falcon-rw-7b 0.535818 \n",
- "38 tiiuae/falcon-7b 0.559636 \n",
- "39 huggyllama/llama-7b 0.541818 \n",
- "40 meta-llama/Llama-2-7b-chat-hf 0.559818 \n",
- "41 meta-llama/Llama-2-7b-hf 0.566727 \n",
+ "29 aisingapore/sealion7b 0.559818 \n",
+ "30 aisingapore/sealion3b 0.559273 \n",
+ "31 togethercomputer/RedPajama-INCITE-7B-Base 0.525455 \n",
+ "32 togethercomputer/RedPajama-INCITE-7B-Instruct 0.528545 \n",
+ "33 togethercomputer/RedPajama-INCITE-7B-Chat 0.535455 \n",
+ "34 facebook/opt-2.7b 0.521818 \n",
+ "35 facebook/opt-6.7b 0.522909 \n",
+ "36 facebook/opt-1.3b 0.521818 \n",
+ "37 tiiuae/falcon-7b-instruct 0.536727 \n",
+ "38 tiiuae/falcon-rw-1b 0.522545 \n",
+ "39 tiiuae/falcon-rw-7b 0.535818 \n",
+ "40 tiiuae/falcon-7b 0.559636 \n",
+ "41 huggyllama/llama-7b 0.541818 \n",
+ "42 meta-llama/Llama-2-7b-chat-hf 0.559818 \n",
+ "43 meta-llama/Llama-2-7b-hf 0.566727 \n",
"\n",
" avg_acc_stderr xcopa (acc) xcopa (acc_stderr) \n",
"0 0.053879 0.559455 0.053879 \n",
@@ -646,22 +664,24 @@
"26 0.039406 0.554000 0.039406 \n",
"27 0.070563 0.622364 0.070563 \n",
"28 0.053116 0.601455 0.053116 \n",
- "29 0.036407 0.525455 0.036407 \n",
- "30 0.036470 0.528545 0.036470 \n",
- "31 0.038723 0.535455 0.038723 \n",
- "32 0.029821 0.521818 0.029821 \n",
- "33 0.027216 0.522909 0.027216 \n",
- "34 0.029112 0.521818 0.029112 \n",
- "35 0.053430 0.536727 0.053430 \n",
- "36 0.029446 0.522545 0.029446 \n",
- "37 0.033185 0.535818 0.033185 \n",
- "38 0.071650 0.559636 0.071650 \n",
- "39 0.040718 0.541818 0.040718 \n",
- "40 0.054954 0.559818 0.054954 \n",
- "41 0.052515 0.566727 0.052515 "
+ "29 0.060680 0.559818 0.060680 \n",
+ "30 0.054490 0.559273 0.054490 \n",
+ "31 0.036407 0.525455 0.036407 \n",
+ "32 0.036470 0.528545 0.036470 \n",
+ "33 0.038723 0.535455 0.038723 \n",
+ "34 0.029821 0.521818 0.029821 \n",
+ "35 0.027216 0.522909 0.027216 \n",
+ "36 0.029112 0.521818 0.029112 \n",
+ "37 0.053430 0.536727 0.053430 \n",
+ "38 0.029446 0.522545 0.029446 \n",
+ "39 0.033185 0.535818 0.033185 \n",
+ "40 0.071650 0.559636 0.071650 \n",
+ "41 0.040718 0.541818 0.040718 \n",
+ "42 0.054954 0.559818 0.054954 \n",
+ "43 0.052515 0.566727 0.052515 "
]
},
- "execution_count": 17,
+ "execution_count": 89,
"metadata": {},
"output_type": "execute_result"
}
@@ -851,27 +871,27 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 90,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "total 17424\n",
- "-rw-r--r--@ 1 picocreator staff 1.0M Feb 28 08:55 bf16-all-results-and-groups.csv\n",
- "-rw-r--r--@ 1 picocreator staff 64K Feb 28 08:55 bf16-eng-focus.csv\n",
- "-rw-r--r--@ 1 picocreator staff 920K Feb 28 08:55 bf16-eng-results.csv\n",
- "-rw-r--r--@ 1 picocreator staff 77K Feb 28 08:55 bf16-eng-summary.csv\n",
- "-rw-r--r--@ 1 picocreator staff 96K Feb 28 08:55 bf16-multilang-results.csv\n",
- "-rw-r--r--@ 1 picocreator staff 14K Feb 28 08:55 bf16-multilang-summary.csv\n",
- "-rw-r--r--@ 1 picocreator staff 64K Feb 28 08:55 bf16-sorted-eng-focus.csv\n",
- "-rw-r--r--@ 1 picocreator staff 920K Feb 28 08:55 bf16-sorted-eng-results.csv\n",
- "-rw-r--r--@ 1 picocreator staff 77K Feb 28 08:55 bf16-sorted-eng-summary.csv\n",
- "-rw-r--r--@ 1 picocreator staff 14K Feb 28 08:55 bf16-sorted-multilang-summary.csv\n",
- "-rw-r--r-- 1 picocreator staff 4.6M Feb 28 08:55 compiled-lm-eval-results.json\n",
- "-rw-r--r--@ 1 picocreator staff 31K Feb 28 08:55 rwkv-x-dev-bf16-sorted-eng-focus.csv\n",
- "-rw-r--r--@ 1 picocreator staff 6.1K Feb 28 08:55 rwkv-x-dev-bf16-sorted-multilang-summary.csv\n"
+ "total 21400\n",
+ "-rw-r--r--@ 1 picocreator staff 1.0M Mar 1 12:43 bf16-all-results-and-groups.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 41K Mar 1 12:43 bf16-eng-focus.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 966K Mar 1 12:43 bf16-eng-results.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 81K Mar 1 12:43 bf16-eng-summary.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 100K Mar 1 12:43 bf16-multilang-results.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 14K Mar 1 12:43 bf16-multilang-summary.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 41K Mar 1 12:43 bf16-sorted-eng-focus.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 966K Mar 1 12:43 bf16-sorted-eng-results.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 81K Mar 1 12:43 bf16-sorted-eng-summary.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 14K Mar 1 12:43 bf16-sorted-multilang-summary.csv\n",
+ "-rw-r--r-- 1 picocreator staff 5.1M Mar 1 12:43 compiled-lm-eval-results.json\n",
+ "-rw-r--r--@ 1 picocreator staff 23K Mar 1 12:43 rwkv-x-dev-bf16-sorted-eng-focus.csv\n",
+ "-rw-r--r--@ 1 picocreator staff 7.8K Mar 1 12:43 rwkv-x-dev-bf16-sorted-multilang-summary.csv\n"
]
}
],
@@ -916,8 +936,13 @@
"eng_grp_sorted.to_csv('summary/bf16-sorted-eng-summary.csv', index=False)\n",
"\n",
"# English focused subset\n",
- "eng_focus_tGrps=[\"anli\", \"glue\", \"truthfulqa\", \"lambada\", \"cmmlu\", \"pythia\", \"mmlu\", \"blimp\", \"record\", \"np_open\", \"piqa\", \"copa\", \"sciq\"]\n",
- "eng_focus_tTest=[\"blimp\", \"arc_*\", \"logiqa\", \"winogrande\", \"openbookqa\", \"hellaswag\", \"blimp\", \"record\", \"np_open\", \"piqa\", \"copa\", \"sciq\"]\n",
+ "eng_focus_mixed=[\"lambda_*\", \"blimp\", \"piqa\", \"copa\", \"sciq\", \"pythia\", \"truthfulqa\", \"record\"] #\"np_open\", \n",
+ "eng_focus_tGrps=[\"anli\", \"glue\", \"lambada\", \"cmmlu\", \"mmlu\" ]\n",
+ "eng_focus_tTest=[\"blimp\", \"arc_*\", \"logiqa\", \"winogrande\", \"openbookqa\", \"hellaswag\"]\n",
+ "\n",
+ "eng_focus_tGrps = eng_focus_tGrps + eng_focus_mixed\n",
+ "eng_focus_tTest = eng_focus_tTest + eng_focus_mixed\n",
+ "\n",
"eng_focus = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=eng_focus_tGrps, inResults=eng_focus_tTest )\n",
"eng_focus_sorted = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=eng_focus_tGrps, inResults=eng_focus_tTest, sort=True )\n",
"eng_focus.to_csv('summary/bf16-eng-focus.csv', index=False)\n",
@@ -927,6 +952,10 @@
"rwkv_eng_focus_sorted = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=eng_focus_tGrps, inResults=eng_focus_tTest, exModels=[], inModels=[\"./rwkv-x-dev/*\", \"rwkv-x-dev/*\", \"RWKV/*\"], sort=True )\n",
"rwkv_eng_focus_sorted.to_csv('summary/rwkv-x-dev-bf16-sorted-eng-focus.csv', index=False)\n",
"\n",
+ "# # Overall results\n",
+ "# rwkv_all_results = generate_result_table( inConfig = { \"dtype\": \"bfloat16\" }, inGroups=[\"*\"], inResults=[\"*\"], inModels=[\"./rwkv-x-dev/*\", \"rwkv-x-dev/*\", \"RWKV/*\"], exModels=[], sort=True )\n",
+ "# rwkv_all_results.to_csv('summary/rwkv-x-dev-bf16-all-results-and-groups.csv', index=False)\n",
+ "\n",
"# List the files\n",
"!ls -lh summary"
]
diff --git a/lm-eval-output/aisingapore/sealion3b/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
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+ "alias": " - blimp_irregular_plural_subject_verb_agreement_1"
+ },
+ "blimp_irregular_plural_subject_verb_agreement_2": {
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+ "alias": " - blimp_irregular_plural_subject_verb_agreement_2"
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+ "blimp_left_branch_island_echo_question": {
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+ "acc_stderr,none": 0.014593284892852632,
+ "alias": " - blimp_left_branch_island_echo_question"
+ },
+ "blimp_left_branch_island_simple_question": {
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+ "alias": " - blimp_left_branch_island_simple_question"
+ },
+ "blimp_matrix_question_npi_licensor_present": {
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+ "acc_stderr,none": 0.014553205687950436,
+ "alias": " - blimp_matrix_question_npi_licensor_present"
+ },
+ "blimp_npi_present_1": {
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+ "alias": " - blimp_npi_present_1"
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+ "blimp_npi_present_2": {
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+ "alias": " - blimp_npi_present_2"
+ },
+ "blimp_only_npi_licensor_present": {
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+ "alias": " - blimp_only_npi_licensor_present"
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+ "blimp_only_npi_scope": {
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+ "alias": " - blimp_only_npi_scope"
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+ "alias": " - blimp_passive_1"
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+ "alias": " - blimp_passive_2"
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+ "alias": " - blimp_principle_A_c_command"
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+ "alias": " - blimp_principle_A_case_1"
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+ "alias": " - blimp_principle_A_case_2"
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+ "alias": " - blimp_principle_A_domain_1"
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+ "alias": " - blimp_principle_A_domain_2"
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+ "alias": " - blimp_principle_A_domain_3"
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+ "blimp_principle_A_reconstruction": {
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+ "alias": " - blimp_principle_A_reconstruction"
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+ "blimp_regular_plural_subject_verb_agreement_1": {
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+ "alias": " - blimp_regular_plural_subject_verb_agreement_1"
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+ "alias": " - blimp_regular_plural_subject_verb_agreement_2"
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+ "blimp_sentential_negation_npi_licensor_present": {
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+ "alias": " - blimp_sentential_negation_npi_licensor_present"
+ },
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+ "alias": " - blimp_sentential_negation_npi_scope"
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+ "blimp_sentential_subject_island": {
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+ "alias": " - blimp_sentential_subject_island"
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+ "alias": " - blimp_superlative_quantifiers_1"
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+ "alias": " - blimp_superlative_quantifiers_2"
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+ "alias": " - blimp_tough_vs_raising_1"
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+ "alias": " - blimp_tough_vs_raising_2"
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+ "alias": " - blimp_transitive"
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+ "alias": " - blimp_wh_island"
+ },
+ "blimp_wh_questions_object_gap": {
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+ "acc_stderr,none": 0.012259457340938577,
+ "alias": " - blimp_wh_questions_object_gap"
+ },
+ "blimp_wh_questions_subject_gap": {
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+ "acc_stderr,none": 0.009276910103103294,
+ "alias": " - blimp_wh_questions_subject_gap"
+ },
+ "blimp_wh_questions_subject_gap_long_distance": {
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+ "acc_stderr,none": 0.010945263761042965,
+ "alias": " - blimp_wh_questions_subject_gap_long_distance"
+ },
+ "blimp_wh_vs_that_no_gap": {
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+ "acc_stderr,none": 0.007212976294639229,
+ "alias": " - blimp_wh_vs_that_no_gap"
+ },
+ "blimp_wh_vs_that_no_gap_long_distance": {
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+ "acc_stderr,none": 0.009144376393151105,
+ "alias": " - blimp_wh_vs_that_no_gap_long_distance"
+ },
+ "blimp_wh_vs_that_with_gap": {
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+ "alias": " - blimp_wh_vs_that_with_gap"
+ },
+ "blimp_wh_vs_that_with_gap_long_distance": {
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+ "alias": " - blimp_wh_vs_that_with_gap_long_distance"
+ }
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+ "groups": {
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+ "blimp_anaphor_gender_agreement": {
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+ "blimp_determiner_noun_agreement_irregular_1": {
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+ "description": "以下是中国关于中国语言文学的单项选择题,请选出其中的正确答案。\n\n",
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+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于计算机网络的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_discrete_mathematics": {
+ "task": "ceval-valid_discrete_mathematics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "discrete_mathematics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于离散数学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_education_science": {
+ "task": "ceval-valid_education_science",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "education_science",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于教育学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ {
+ "metric": "acc_norm",
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ },
+ "ceval-valid_electrical_engineer": {
+ "task": "ceval-valid_electrical_engineer",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "electrical_engineer",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于注册电气工程师的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
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+ }
+ },
+ "ceval-valid_environmental_impact_assessment_engineer": {
+ "task": "ceval-valid_environmental_impact_assessment_engineer",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "environmental_impact_assessment_engineer",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于环境影响评价工程师的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metric_list": [
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+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ },
+ "ceval-valid_fire_engineer": {
+ "task": "ceval-valid_fire_engineer",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "fire_engineer",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
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+ "description": "以下是中国关于注册消防工程师的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
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+ "fewshot_config": {
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+ "ceval-valid_high_school_biology": {
+ "task": "ceval-valid_high_school_biology",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_biology",
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+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
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+ "description": "以下是中国关于高中生物的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
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+ "metric_list": [
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+ "should_decontaminate": false,
+ "metadata": {
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+ "ceval-valid_high_school_chemistry": {
+ "task": "ceval-valid_high_school_chemistry",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_chemistry",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于高中化学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
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+ "fewshot_config": {
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+ "metric_list": [
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+ "higher_is_better": true
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ },
+ "ceval-valid_high_school_chinese": {
+ "task": "ceval-valid_high_school_chinese",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_chinese",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于高中语文的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
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+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ "metric": "acc_norm",
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+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ },
+ "ceval-valid_high_school_geography": {
+ "task": "ceval-valid_high_school_geography",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_geography",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于高中地理的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ {
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ ],
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+ "should_decontaminate": false,
+ "metadata": {
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+ },
+ "ceval-valid_high_school_history": {
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+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_history",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于高中历史的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_high_school_mathematics": {
+ "task": "ceval-valid_high_school_mathematics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_mathematics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于高中数学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_high_school_physics": {
+ "task": "ceval-valid_high_school_physics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_physics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于高中物理的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_high_school_politics": {
+ "task": "ceval-valid_high_school_politics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "high_school_politics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于高中政治的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_ideological_and_moral_cultivation": {
+ "task": "ceval-valid_ideological_and_moral_cultivation",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "ideological_and_moral_cultivation",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于思想道德修养与法律基础的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_law": {
+ "task": "ceval-valid_law",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "law",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于法学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_legal_professional": {
+ "task": "ceval-valid_legal_professional",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "legal_professional",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于法律职业资格的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_logic": {
+ "task": "ceval-valid_logic",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "logic",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于逻辑学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
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+ {
+ "metric": "acc_norm",
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+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_mao_zedong_thought": {
+ "task": "ceval-valid_mao_zedong_thought",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "mao_zedong_thought",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于毛泽东思想和中国特色社会主义理论体系概论的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_marxism": {
+ "task": "ceval-valid_marxism",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "marxism",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于马克思主义基本原理的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_metrology_engineer": {
+ "task": "ceval-valid_metrology_engineer",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "metrology_engineer",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于注册计量师的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
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+ },
+ "ceval-valid_middle_school_biology": {
+ "task": "ceval-valid_middle_school_biology",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "middle_school_biology",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于初中生物的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
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+ },
+ "ceval-valid_middle_school_chemistry": {
+ "task": "ceval-valid_middle_school_chemistry",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "middle_school_chemistry",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于初中化学的单项选择题,请选出其中的正确答案。\n\n",
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+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metadata": {
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+ },
+ "ceval-valid_middle_school_geography": {
+ "task": "ceval-valid_middle_school_geography",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "middle_school_geography",
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+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于初中地理的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metadata": {
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+ },
+ "ceval-valid_middle_school_history": {
+ "task": "ceval-valid_middle_school_history",
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+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "middle_school_history",
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+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于初中历史的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
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+ "fewshot_config": {
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+ "metadata": {
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+ },
+ "ceval-valid_middle_school_mathematics": {
+ "task": "ceval-valid_middle_school_mathematics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "middle_school_mathematics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于初中数学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ "aggregation": "mean",
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+ {
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+ "higher_is_better": true
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+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
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+ },
+ "ceval-valid_middle_school_physics": {
+ "task": "ceval-valid_middle_school_physics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "middle_school_physics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于初中物理的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_middle_school_politics": {
+ "task": "ceval-valid_middle_school_politics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "middle_school_politics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于初中政治的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_modern_chinese_history": {
+ "task": "ceval-valid_modern_chinese_history",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "modern_chinese_history",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于近代史纲要的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_operating_system": {
+ "task": "ceval-valid_operating_system",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "operating_system",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于操作系统的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_physician": {
+ "task": "ceval-valid_physician",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "physician",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于医师资格的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_plant_protection": {
+ "task": "ceval-valid_plant_protection",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "plant_protection",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于植物保护的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_probability_and_statistics": {
+ "task": "ceval-valid_probability_and_statistics",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "probability_and_statistics",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于概率统计的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_professional_tour_guide": {
+ "task": "ceval-valid_professional_tour_guide",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "professional_tour_guide",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于导游资格的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_sports_science": {
+ "task": "ceval-valid_sports_science",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "sports_science",
+ "validation_split": "val",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是中国关于体育学的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
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+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
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+ },
+ "ceval-valid_tax_accountant": {
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+ "doc_to_choice": [
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+ "description": "以下是中国关于税务师的单项选择题,请选出其中的正确答案。\n\n",
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+ "fewshot_delimiter": "\n\n",
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+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
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+ "validation_split": "val",
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+ "doc_to_choice": [
+ "A",
+ "B",
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+ "D"
+ ],
+ "description": "以下是中国关于教师资格的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "ceval-valid_urban_and_rural_planner": {
+ "task": "ceval-valid_urban_and_rural_planner",
+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "urban_and_rural_planner",
+ "validation_split": "val",
+ "fewshot_split": "dev",
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+ "doc_to_choice": [
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+ "C",
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+ "description": "以下是中国关于注册城乡规划师的单项选择题,请选出其中的正确答案。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "ceval-valid_veterinary_medicine": {
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+ "group": "ceval-valid",
+ "dataset_path": "ceval/ceval-exam",
+ "dataset_name": "veterinary_medicine",
+ "validation_split": "val",
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+ "doc_to_text": "{{question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
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+ "doc_to_choice": [
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+ "D"
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+ "description": "以下是中国关于兽医学的单项选择题,请选出其中的正确答案。\n\n",
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+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+}
\ No newline at end of file
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+ "doc_to_choice": [
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+ "description": "以下是关于农学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
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+ "doc_to_choice": [
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+ "description": "以下是关于解剖学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "dataset_name": "ancient_chinese",
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+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "C",
+ "D"
+ ],
+ "description": "以下是关于古汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "dataset_name": "arts",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于艺术学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "astronomy",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
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+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于天文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "dataset_name": "business_ethics",
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+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于商业伦理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ "output_type": "multiple_choice",
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+ "group": "cmmlu",
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+ "dataset_name": "chinese_civil_service_exam",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
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+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
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+ "description": "以下是关于中国公务员考试的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "output_type": "multiple_choice",
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+ "C",
+ "D"
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+ "description": "以下是关于中国驾驶规则的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metric_list": [
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+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_food_culture",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国饮食文化的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_foreign_policy": {
+ "task": "cmmlu_chinese_foreign_policy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国外交政策的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_history": {
+ "task": "cmmlu_chinese_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_literature": {
+ "task": "cmmlu_chinese_literature",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_literature",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_teacher_qualification": {
+ "task": "cmmlu_chinese_teacher_qualification",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_teacher_qualification",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国教师资格的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_clinical_knowledge": {
+ "task": "cmmlu_clinical_knowledge",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于临床知识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_actuarial_science": {
+ "task": "cmmlu_college_actuarial_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_actuarial_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学精算学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_education": {
+ "task": "cmmlu_college_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_engineering_hydrology": {
+ "task": "cmmlu_college_engineering_hydrology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_engineering_hydrology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学工程水文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_law": {
+ "task": "cmmlu_college_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学法律的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_mathematics": {
+ "task": "cmmlu_college_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medical_statistics": {
+ "task": "cmmlu_college_medical_statistics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medical_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学统计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medicine": {
+ "task": "cmmlu_college_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_science": {
+ "task": "cmmlu_computer_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_security": {
+ "task": "cmmlu_computer_security",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机安全的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_conceptual_physics": {
+ "task": "cmmlu_conceptual_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于概念物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_construction_project_management": {
+ "task": "cmmlu_construction_project_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "construction_project_management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于建设工程管理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_economics": {
+ "task": "cmmlu_economics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "economics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于经济学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_education": {
+ "task": "cmmlu_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_electrical_engineering": {
+ "task": "cmmlu_electrical_engineering",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于电气工程的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_chinese": {
+ "task": "cmmlu_elementary_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学语文的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_commonsense": {
+ "task": "cmmlu_elementary_commonsense",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_commonsense",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学常识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_information_and_technology": {
+ "task": "cmmlu_elementary_information_and_technology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_information_and_technology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学信息技术的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_mathematics": {
+ "task": "cmmlu_elementary_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于初等数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_ethnology": {
+ "task": "cmmlu_ethnology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "ethnology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于民族学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_food_science": {
+ "task": "cmmlu_food_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "food_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于食品科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_genetics": {
+ "task": "cmmlu_genetics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于遗传学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_global_facts": {
+ "task": "cmmlu_global_facts",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于全球事实的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_biology": {
+ "task": "cmmlu_high_school_biology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中生物的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_chemistry": {
+ "task": "cmmlu_high_school_chemistry",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中化学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_geography": {
+ "task": "cmmlu_high_school_geography",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中地理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_mathematics": {
+ "task": "cmmlu_high_school_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_physics": {
+ "task": "cmmlu_high_school_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_politics": {
+ "task": "cmmlu_high_school_politics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中政治的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_human_sexuality": {
+ "task": "cmmlu_human_sexuality",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于人类性行为的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_international_law": {
+ "task": "cmmlu_international_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于国际法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_journalism": {
+ "task": "cmmlu_journalism",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "journalism",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于新闻学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_jurisprudence": {
+ "task": "cmmlu_jurisprudence",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_legal_and_moral_basis": {
+ "task": "cmmlu_legal_and_moral_basis",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "legal_and_moral_basis",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法律与道德基础的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_logical": {
+ "task": "cmmlu_logical",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "logical",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于逻辑学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_machine_learning": {
+ "task": "cmmlu_machine_learning",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于机器学习的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_management": {
+ "task": "cmmlu_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于管理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marketing": {
+ "task": "cmmlu_marketing",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于市场营销的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marxist_theory": {
+ "task": "cmmlu_marxist_theory",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marxist_theory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于马克思主义理论的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_modern_chinese": {
+ "task": "cmmlu_modern_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "modern_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于现代汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_nutrition": {
+ "task": "cmmlu_nutrition",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于营养学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_philosophy": {
+ "task": "cmmlu_philosophy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于哲学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_accounting": {
+ "task": "cmmlu_professional_accounting",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业会计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_law": {
+ "task": "cmmlu_professional_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_medicine": {
+ "task": "cmmlu_professional_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_psychology": {
+ "task": "cmmlu_professional_psychology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业心理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_public_relations": {
+ "task": "cmmlu_public_relations",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于公共关系的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_security_study": {
+ "task": "cmmlu_security_study",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "security_study",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于安全研究的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sociology": {
+ "task": "cmmlu_sociology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于社会学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
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+ "higher_is_better": true
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+ "metric": "acc_norm",
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+ }
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sports_science": {
+ "task": "cmmlu_sports_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sports_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于体育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metadata": {
+ "version": 0.0
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+ },
+ "cmmlu_traditional_chinese_medicine": {
+ "task": "cmmlu_traditional_chinese_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "traditional_chinese_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中医中药的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "higher_is_better": true
+ }
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_virology": {
+ "task": "cmmlu_virology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于病毒学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_history",
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+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
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+ "description": "以下是关于世界历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "aggregation": "mean",
+ "higher_is_better": true
+ },
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+ "cmmlu_world_religions": {
+ "task": "cmmlu_world_religions",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界宗教的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "higher_is_better": true
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+ {
+ "metric": "acc_norm",
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
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+ "alias": "cola"
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+ "group": "glue",
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+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "{{sentence}}\nQuestion: Does this sentence make sense?\nAnswer:",
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+ "doc_to_choice": [
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+ "target_delimiter": " ",
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+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
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+++ b/lm-eval-output/aisingapore/sealion3b/crows_pairs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,1052 @@
+{
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+ "should_decontaminate": false,
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+ "crows_pairs_english_gender": {
+ "task": "crows_pairs_english_gender",
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+ "crows_pairs",
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+ "crows_pairs",
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+ "loglikelihood"
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+ "metadata": {
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+ "crows_pairs_english_physical_appearance": {
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+ "group": [
+ "crows_pairs",
+ "social_bias",
+ "loglikelihood"
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+ "crows_pairs_english_race_color": {
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+ "group": [
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+ "loglikelihood"
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+ "loglikelihood"
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+ "should_decontaminate": false,
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+ "crows_pairs_english_sexual_orientation": {
+ "task": "crows_pairs_english_sexual_orientation",
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+ "crows_pairs",
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+ "loglikelihood"
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+ "should_decontaminate": false,
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+ "crows_pairs_english_socioeconomic": {
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+ "crows_pairs",
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+ "loglikelihood"
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+ "dataset_path": "BigScienceBiasEval/crows_pairs_multilingual",
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+ "crows_pairs",
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+ "loglikelihood"
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+ "doc_to_choice": "def doc_to_choice(doc):\n return [doc[\"sent_more\"], doc[\"sent_less\"]]\n",
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+ "crows_pairs_french_age": {
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+ "crows_pairs_french_autre": {
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+ "crows_pairs_french_disability": {
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+ "crows_pairs",
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+ "dataset_path": "BigScienceBiasEval/crows_pairs_multilingual",
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+ "process_docs": "def filter_disability(dataset: datasets.Dataset) -> datasets.Dataset:\n return filter_dataset(dataset, \"disability\")\n",
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+ "doc_to_target": 0,
+ "doc_to_choice": "def doc_to_choice(doc):\n return [doc[\"sent_more\"], doc[\"sent_less\"]]\n",
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+ {
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
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+ "crows_pairs_french_gender": {
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+ "group": [
+ "crows_pairs",
+ "social_bias",
+ "loglikelihood"
+ ],
+ "dataset_path": "BigScienceBiasEval/crows_pairs_multilingual",
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+ "doc_to_target": 0,
+ "doc_to_choice": "def doc_to_choice(doc):\n return [doc[\"sent_more\"], doc[\"sent_less\"]]\n",
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+ {
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+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
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+ "crows_pairs_french_nationality": {
+ "task": "crows_pairs_french_nationality",
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+ "crows_pairs",
+ "social_bias",
+ "loglikelihood"
+ ],
+ "dataset_path": "BigScienceBiasEval/crows_pairs_multilingual",
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+ "crows_pairs_french_physical_appearance": {
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+ "loglikelihood"
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+ "crows_pairs_french_race_color": {
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+ "loglikelihood"
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+ "crows_pairs_french_religion": {
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+ "crows_pairs_french_sexual_orientation": {
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+ "crows_pairs_french_socioeconomic": {
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+ "should_decontaminate": false,
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+ "versions": {
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+ "crows_pairs_english_age": 1.0,
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+ "crows_pairs_english_race_color": 1.0,
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+ "crows_pairs_french_sexual_orientation": 1.0,
+ "crows_pairs_french_socioeconomic": 1.0
+ },
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+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion3b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
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+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: \n Question: \n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"text\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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diff --git a/lm-eval-output/aisingapore/sealion3b/logiqa2/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/logiqa2/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/mathqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/mathqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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diff --git a/lm-eval-output/aisingapore/sealion3b/mc_taco/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/mc_taco/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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diff --git a/lm-eval-output/aisingapore/sealion3b/mc_taco/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/mc_taco/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/medmcqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/medmcqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [doc[\"opa\"], doc[\"opb\"], doc[\"opc\"], doc[\"opd\"]]\n option_choices = {'A': choices[0], 'B': choices[1], 'C': choices[2], 'D': choices[3]}\n\n prompt = \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in option_choices.items():\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
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diff --git a/lm-eval-output/aisingapore/sealion3b/medmcqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/medmcqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/medqa_4options/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/medqa_4options/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "mmlu_social_sciences": {
+ "alias": " - social_sciences",
+ "acc,none": 0.2349691257718557,
+ "acc_stderr,none": 0.036464942583659364
+ },
+ "mmlu_econometrics": {
+ "alias": " - econometrics",
+ "acc,none": 0.2631578947368421,
+ "acc_stderr,none": 0.04142439719489362
+ },
+ "mmlu_high_school_geography": {
+ "alias": " - high_school_geography",
+ "acc,none": 0.23737373737373738,
+ "acc_stderr,none": 0.0303137105381989
+ },
+ "mmlu_high_school_government_and_politics": {
+ "alias": " - high_school_government_and_politics",
+ "acc,none": 0.21761658031088082,
+ "acc_stderr,none": 0.02977866303775296
+ },
+ "mmlu_high_school_macroeconomics": {
+ "alias": " - high_school_macroeconomics",
+ "acc,none": 0.2153846153846154,
+ "acc_stderr,none": 0.020843034557462874
+ },
+ "mmlu_high_school_microeconomics": {
+ "alias": " - high_school_microeconomics",
+ "acc,none": 0.2184873949579832,
+ "acc_stderr,none": 0.02684151432295894
+ },
+ "mmlu_high_school_psychology": {
+ "alias": " - high_school_psychology",
+ "acc,none": 0.1871559633027523,
+ "acc_stderr,none": 0.01672268452620014
+ },
+ "mmlu_human_sexuality": {
+ "alias": " - human_sexuality",
+ "acc,none": 0.29770992366412213,
+ "acc_stderr,none": 0.04010358942462203
+ },
+ "mmlu_professional_psychology": {
+ "alias": " - professional_psychology",
+ "acc,none": 0.24673202614379086,
+ "acc_stderr,none": 0.017440820367402507
+ },
+ "mmlu_public_relations": {
+ "alias": " - public_relations",
+ "acc,none": 0.22727272727272727,
+ "acc_stderr,none": 0.04013964554072774
+ },
+ "mmlu_security_studies": {
+ "alias": " - security_studies",
+ "acc,none": 0.2571428571428571,
+ "acc_stderr,none": 0.02797982353874455
+ },
+ "mmlu_sociology": {
+ "alias": " - sociology",
+ "acc,none": 0.2835820895522388,
+ "acc_stderr,none": 0.03187187537919797
+ },
+ "mmlu_us_foreign_policy": {
+ "alias": " - us_foreign_policy",
+ "acc,none": 0.31,
+ "acc_stderr,none": 0.04648231987117316
+ },
+ "mmlu_stem": {
+ "alias": " - stem",
+ "acc,none": 0.2261338407865525,
+ "acc_stderr,none": 0.03792556864697487
+ },
+ "mmlu_abstract_algebra": {
+ "alias": " - abstract_algebra",
+ "acc,none": 0.22,
+ "acc_stderr,none": 0.04163331998932269
+ },
+ "mmlu_anatomy": {
+ "alias": " - anatomy",
+ "acc,none": 0.21481481481481482,
+ "acc_stderr,none": 0.03547854198560824
+ },
+ "mmlu_astronomy": {
+ "alias": " - astronomy",
+ "acc,none": 0.23026315789473684,
+ "acc_stderr,none": 0.034260594244031654
+ },
+ "mmlu_college_biology": {
+ "alias": " - college_biology",
+ "acc,none": 0.2222222222222222,
+ "acc_stderr,none": 0.03476590104304134
+ },
+ "mmlu_college_chemistry": {
+ "alias": " - college_chemistry",
+ "acc,none": 0.24,
+ "acc_stderr,none": 0.042923469599092816
+ },
+ "mmlu_college_computer_science": {
+ "alias": " - college_computer_science",
+ "acc,none": 0.27,
+ "acc_stderr,none": 0.0446196043338474
+ },
+ "mmlu_college_mathematics": {
+ "alias": " - college_mathematics",
+ "acc,none": 0.23,
+ "acc_stderr,none": 0.04229525846816507
+ },
+ "mmlu_college_physics": {
+ "alias": " - college_physics",
+ "acc,none": 0.2549019607843137,
+ "acc_stderr,none": 0.04336432707993176
+ },
+ "mmlu_computer_security": {
+ "alias": " - computer_security",
+ "acc,none": 0.24,
+ "acc_stderr,none": 0.042923469599092816
+ },
+ "mmlu_conceptual_physics": {
+ "alias": " - conceptual_physics",
+ "acc,none": 0.25957446808510637,
+ "acc_stderr,none": 0.028659179374292323
+ },
+ "mmlu_electrical_engineering": {
+ "alias": " - electrical_engineering",
+ "acc,none": 0.2482758620689655,
+ "acc_stderr,none": 0.03600105692727771
+ },
+ "mmlu_elementary_mathematics": {
+ "alias": " - elementary_mathematics",
+ "acc,none": 0.20634920634920634,
+ "acc_stderr,none": 0.02084229093011467
+ },
+ "mmlu_high_school_biology": {
+ "alias": " - high_school_biology",
+ "acc,none": 0.22580645161290322,
+ "acc_stderr,none": 0.023785577884181012
+ },
+ "mmlu_high_school_chemistry": {
+ "alias": " - high_school_chemistry",
+ "acc,none": 0.1921182266009852,
+ "acc_stderr,none": 0.02771931570961477
+ },
+ "mmlu_high_school_computer_science": {
+ "alias": " - high_school_computer_science",
+ "acc,none": 0.25,
+ "acc_stderr,none": 0.04351941398892446
+ },
+ "mmlu_high_school_mathematics": {
+ "alias": " - high_school_mathematics",
+ "acc,none": 0.22962962962962963,
+ "acc_stderr,none": 0.025644108639267603
+ },
+ "mmlu_high_school_physics": {
+ "alias": " - high_school_physics",
+ "acc,none": 0.2251655629139073,
+ "acc_stderr,none": 0.03410435282008936
+ },
+ "mmlu_high_school_statistics": {
+ "alias": " - high_school_statistics",
+ "acc,none": 0.1574074074074074,
+ "acc_stderr,none": 0.02483717351824239
+ },
+ "mmlu_machine_learning": {
+ "alias": " - machine_learning",
+ "acc,none": 0.2857142857142857,
+ "acc_stderr,none": 0.04287858751340456
+ }
+ },
+ "groups": {
+ "mmlu": {
+ "acc,none": 0.24305654465175902,
+ "acc_stderr,none": 0.036930868857829716,
+ "alias": "mmlu"
+ },
+ "mmlu_humanities": {
+ "alias": " - humanities",
+ "acc,none": 0.24973432518597238,
+ "acc_stderr,none": 0.03290048214291232
+ },
+ "mmlu_other": {
+ "alias": " - other",
+ "acc,none": 0.2581268104280656,
+ "acc_stderr,none": 0.03745195966789567
+ },
+ "mmlu_social_sciences": {
+ "alias": " - social_sciences",
+ "acc,none": 0.2349691257718557,
+ "acc_stderr,none": 0.036464942583659364
+ },
+ "mmlu_stem": {
+ "alias": " - stem",
+ "acc,none": 0.2261338407865525,
+ "acc_stderr,none": 0.03792556864697487
+ }
+ },
+ "configs": {
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ }
+ },
+ "versions": {
+ "mmlu": "N/A",
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+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
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+ "mmlu_conceptual_physics": 0.0,
+ "mmlu_econometrics": 0.0,
+ "mmlu_electrical_engineering": 0.0,
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+ "mmlu_high_school_world_history": 0.0,
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+ "mmlu_moral_disputes": 0.0,
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+ "mmlu_other": "N/A",
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+ "mmlu_virology": 0.0,
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+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion3b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 8
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+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
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diff --git a/lm-eval-output/aisingapore/sealion3b/mnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/mnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "acc,none": 0.35476311767702495,
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+ "alias": "mnli"
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+ "group": "glue",
+ "dataset_path": "glue",
+ "dataset_name": "mnli",
+ "training_split": "train",
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+ "target_delimiter": " ",
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+ "should_decontaminate": false,
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diff --git a/lm-eval-output/aisingapore/sealion3b/mnli_mismatch/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/mnli_mismatch/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "mnli_mismatch": {
+ "acc,none": 0.35465825874694873,
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+ "alias": "mnli_mismatch"
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+ "task": "mnli_mismatch",
+ "group": "glue",
+ "dataset_path": "glue",
+ "dataset_name": "mnli",
+ "training_split": "train",
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diff --git a/lm-eval-output/aisingapore/sealion3b/mrpc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/mrpc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "mrpc"
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+ "results": {
+ "multimedqa": {
+ "alias": "stem",
+ "acc,none": 0.2841731724627395,
+ "acc_stderr,none": 0.09107735690942864,
+ "acc_norm,none": 0.25666432823218555,
+ "acc_norm_stderr,none": 8.551637421340022e-05
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+ "acc_norm,none": 0.25388477169495577,
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+ "alias": " - medmcqa"
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+ "acc_norm,none": 0.2615868028279654,
+ "acc_norm_stderr,none": 0.012322932915507637,
+ "alias": " - medqa_4options"
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+ "alias": " - anatomy (mmlu)",
+ "acc,none": 0.24444444444444444,
+ "acc_stderr,none": 0.037125378336148665
+ },
+ "mmlu_clinical_knowledge": {
+ "alias": " - clinical_knowledge (mmlu)",
+ "acc,none": 0.27169811320754716,
+ "acc_stderr,none": 0.027377706624670713
+ },
+ "mmlu_college_biology": {
+ "alias": " - college_biology (mmlu)",
+ "acc,none": 0.3055555555555556,
+ "acc_stderr,none": 0.03852084696008534
+ },
+ "mmlu_college_medicine": {
+ "alias": " - college_medicine (mmlu)",
+ "acc,none": 0.2658959537572254,
+ "acc_stderr,none": 0.03368762932259431
+ },
+ "mmlu_medical_genetics": {
+ "alias": " - medical_genetics (mmlu)",
+ "acc,none": 0.33,
+ "acc_stderr,none": 0.047258156262526045
+ },
+ "mmlu_professional_medicine": {
+ "alias": " - professional_medicine (mmlu)",
+ "acc,none": 0.23161764705882354,
+ "acc_stderr,none": 0.025626533803777562
+ },
+ "pubmedqa": {
+ "acc,none": 0.632,
+ "acc_stderr,none": 0.02158898256835354,
+ "alias": " - pubmedqa"
+ }
+ },
+ "groups": {
+ "multimedqa": {
+ "alias": "stem",
+ "acc,none": 0.2841731724627395,
+ "acc_stderr,none": 0.09107735690942864,
+ "acc_norm,none": 0.25666432823218555,
+ "acc_norm_stderr,none": 8.551637421340022e-05
+ }
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+ "configs": {
+ "medmcqa": {
+ "task": "medmcqa",
+ "dataset_path": "medmcqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "validation",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [doc[\"opa\"], doc[\"opb\"], doc[\"opc\"], doc[\"opd\"]]\n option_choices = {'A': choices[0], 'B': choices[1], 'C': choices[2], 'D': choices[3]}\n\n prompt = \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in option_choices.items():\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
+ "doc_to_target": "cop",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{question}}"
+ },
+ "medqa_4options": {
+ "task": "medqa_4options",
+ "dataset_path": "GBaker/MedQA-USMLE-4-options-hf",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n option_choices = {'A': doc[\"ending0\"], 'B': doc[\"ending1\"], 'C': doc[\"ending2\"], 'D': doc[\"ending3\"]}\n answers = \"\".join((f\"{k}. {v}\\n\") for k, v in option_choices.items())\n return f\"Question: {doc['sent1']}\\n{answers}Answer:\"\n",
+ "doc_to_target": "def doc_to_target(doc) -> int:\n return doc[\"label\"]\n",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy (mmlu)",
+ "group": "multimedqa",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
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+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge (mmlu)",
+ "group": "multimedqa",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
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+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology (mmlu)",
+ "group": "multimedqa",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
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+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine (mmlu)",
+ "group": "multimedqa",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
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+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics (mmlu)",
+ "group": "multimedqa",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
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+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
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+ "task_alias": "professional_medicine (mmlu)",
+ "group": "multimedqa",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "pubmedqa": {
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+ "dataset_name": "pubmed_qa_labeled_fold0_source",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n ctxs = \"\\n\".join(doc[\"CONTEXTS\"])\n return \"Abstract: {}\\nQuestion: {}\\nAnswer:\".format(\n ctxs,\n doc[\"QUESTION\"],\n )\n",
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+ "yes",
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+ "maybe"
+ ],
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+ "target_delimiter": " ",
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+ "batch_size": "auto",
+ "batch_sizes": [
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+}
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diff --git a/lm-eval-output/aisingapore/sealion3b/multimedqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/multimedqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/multirc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/multirc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "multirc"
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+ "configs": {
+ "multirc": {
+ "task": "multirc",
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+ "super-glue-lm-eval-v1"
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diff --git a/lm-eval-output/aisingapore/sealion3b/multirc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/multirc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/mutual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/mutual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+{
+ "results": {
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+ "r@2,none": 0.43340857787810383,
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+ "mrr,none": 0.670428893905192,
+ "mrr_stderr,none": 0.010392183579316521,
+ "alias": "mutual"
+ }
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+ "configs": {
+ "mutual": {
+ "task": "mutual",
+ "dataset_path": "EleutherAI/mutual",
+ "dataset_name": "mutual",
+ "training_split": "train",
+ "validation_split": "validation",
+ "process_docs": "def process_docs(dataset):\n def _detokenize(text):\n text = text.replace(\" '\", \"'\")\n text = text.replace(\" \\n\", \"\\n\")\n text = text.replace(\"\\n \", \"\\n\")\n text = text.replace(\" n't\", \"n't\")\n text = text.replace(\"`` \", '\"')\n text = text.replace(\"''\", '\"')\n # punctuation\n text = text.replace(\" :\", \":\")\n text = text.replace(\" ;\", \";\")\n text = text.replace(\" !\", \"!\")\n text = text.replace(\" ?\", \"?\")\n text = text.replace(\" ,\", \",\")\n text = text.replace(\" .\", \".\")\n return text\n\n def _process(doc):\n return {\n \"article\": _detokenize(doc[\"article\"]),\n \"options\": [_detokenize(option) for option in doc[\"options\"]],\n }\n\n return dataset.map(_process)\n",
+ "doc_to_text": "{{article}}",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(answers)}}",
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+ "task": "blimp_wh_questions_object_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_questions_object_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_questions_subject_gap": {
+ "task": "blimp_wh_questions_subject_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_questions_subject_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_questions_subject_gap_long_distance": {
+ "task": "blimp_wh_questions_subject_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_questions_subject_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap": {
+ "task": "blimp_wh_vs_that_no_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap_long_distance": {
+ "task": "blimp_wh_vs_that_no_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap": {
+ "task": "blimp_wh_vs_that_with_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap_long_distance": {
+ "task": "blimp_wh_vs_that_with_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "lambada_openai": {
+ "task": "lambada_openai",
+ "group": [
+ "lambada"
+ ],
+ "dataset_path": "EleutherAI/lambada_openai",
+ "dataset_name": "default",
+ "test_split": "test",
+ "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+ "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "perplexity",
+ "aggregation": "perplexity",
+ "higher_is_better": false
+ },
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "loglikelihood",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{text}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "logiqa": {
+ "task": "logiqa",
+ "dataset_path": "EleutherAI/logiqa",
+ "dataset_name": "logiqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: \n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
+ "doc_to_target": "def doc_to_target(doc) -> int:\n choices = [\"a\", \"b\", \"c\", \"d\"]\n return choices.index(doc[\"label\"].strip())\n",
+ "doc_to_choice": "{{options}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{context}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "piqa": {
+ "task": "piqa",
+ "dataset_path": "piqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Question: {{goal}}\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[sol1, sol2]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "goal",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "sciq": {
+ "task": "sciq",
+ "dataset_path": "sciq",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
+ "doc_to_target": 3,
+ "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{support}} {{question}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "word_perplexity"
+ },
+ {
+ "metric": "byte_perplexity"
+ },
+ {
+ "metric": "bits_per_byte"
+ }
+ ],
+ "output_type": "loglikelihood_rolling",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wsc": {
+ "task": "wsc",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wsc.fixed",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "ai2_arc": "N/A",
+ "arc_challenge": 1.0,
+ "arc_easy": 1.0,
+ "blimp": "N/A",
+ "blimp_adjunct_island": 1.0,
+ "blimp_anaphor_gender_agreement": 1.0,
+ "blimp_anaphor_number_agreement": 1.0,
+ "blimp_animate_subject_passive": 1.0,
+ "blimp_animate_subject_trans": 1.0,
+ "blimp_causative": 1.0,
+ "blimp_complex_NP_island": 1.0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 1.0,
+ "blimp_coordinate_structure_constraint_object_extraction": 1.0,
+ "blimp_determiner_noun_agreement_1": 1.0,
+ "blimp_determiner_noun_agreement_2": 1.0,
+ "blimp_determiner_noun_agreement_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 1.0,
+ "blimp_distractor_agreement_relational_noun": 1.0,
+ "blimp_distractor_agreement_relative_clause": 1.0,
+ "blimp_drop_argument": 1.0,
+ "blimp_ellipsis_n_bar_1": 1.0,
+ "blimp_ellipsis_n_bar_2": 1.0,
+ "blimp_existential_there_object_raising": 1.0,
+ "blimp_existential_there_quantifiers_1": 1.0,
+ "blimp_existential_there_quantifiers_2": 1.0,
+ "blimp_existential_there_subject_raising": 1.0,
+ "blimp_expletive_it_object_raising": 1.0,
+ "blimp_inchoative": 1.0,
+ "blimp_intransitive": 1.0,
+ "blimp_irregular_past_participle_adjectives": 1.0,
+ "blimp_irregular_past_participle_verbs": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_left_branch_island_echo_question": 1.0,
+ "blimp_left_branch_island_simple_question": 1.0,
+ "blimp_matrix_question_npi_licensor_present": 1.0,
+ "blimp_npi_present_1": 1.0,
+ "blimp_npi_present_2": 1.0,
+ "blimp_only_npi_licensor_present": 1.0,
+ "blimp_only_npi_scope": 1.0,
+ "blimp_passive_1": 1.0,
+ "blimp_passive_2": 1.0,
+ "blimp_principle_A_c_command": 1.0,
+ "blimp_principle_A_case_1": 1.0,
+ "blimp_principle_A_case_2": 1.0,
+ "blimp_principle_A_domain_1": 1.0,
+ "blimp_principle_A_domain_2": 1.0,
+ "blimp_principle_A_domain_3": 1.0,
+ "blimp_principle_A_reconstruction": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_sentential_negation_npi_licensor_present": 1.0,
+ "blimp_sentential_negation_npi_scope": 1.0,
+ "blimp_sentential_subject_island": 1.0,
+ "blimp_superlative_quantifiers_1": 1.0,
+ "blimp_superlative_quantifiers_2": 1.0,
+ "blimp_tough_vs_raising_1": 1.0,
+ "blimp_tough_vs_raising_2": 1.0,
+ "blimp_transitive": 1.0,
+ "blimp_wh_island": 1.0,
+ "blimp_wh_questions_object_gap": 1.0,
+ "blimp_wh_questions_subject_gap": 1.0,
+ "blimp_wh_questions_subject_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_no_gap": 1.0,
+ "blimp_wh_vs_that_no_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_with_gap": 1.0,
+ "blimp_wh_vs_that_with_gap_long_distance": 1.0,
+ "lambada_openai": 1.0,
+ "logiqa": 1.0,
+ "mmlu": "N/A",
+ "mmlu_abstract_algebra": 0.0,
+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
+ "mmlu_college_computer_science": 0.0,
+ "mmlu_college_mathematics": 0.0,
+ "mmlu_college_medicine": 0.0,
+ "mmlu_college_physics": 0.0,
+ "mmlu_computer_security": 0.0,
+ "mmlu_conceptual_physics": 0.0,
+ "mmlu_econometrics": 0.0,
+ "mmlu_electrical_engineering": 0.0,
+ "mmlu_elementary_mathematics": 0.0,
+ "mmlu_formal_logic": 0.0,
+ "mmlu_global_facts": 0.0,
+ "mmlu_high_school_biology": 0.0,
+ "mmlu_high_school_chemistry": 0.0,
+ "mmlu_high_school_computer_science": 0.0,
+ "mmlu_high_school_european_history": 0.0,
+ "mmlu_high_school_geography": 0.0,
+ "mmlu_high_school_government_and_politics": 0.0,
+ "mmlu_high_school_macroeconomics": 0.0,
+ "mmlu_high_school_mathematics": 0.0,
+ "mmlu_high_school_microeconomics": 0.0,
+ "mmlu_high_school_physics": 0.0,
+ "mmlu_high_school_psychology": 0.0,
+ "mmlu_high_school_statistics": 0.0,
+ "mmlu_high_school_us_history": 0.0,
+ "mmlu_high_school_world_history": 0.0,
+ "mmlu_human_aging": 0.0,
+ "mmlu_human_sexuality": 0.0,
+ "mmlu_humanities": "N/A",
+ "mmlu_international_law": 0.0,
+ "mmlu_jurisprudence": 0.0,
+ "mmlu_logical_fallacies": 0.0,
+ "mmlu_machine_learning": 0.0,
+ "mmlu_management": 0.0,
+ "mmlu_marketing": 0.0,
+ "mmlu_medical_genetics": 0.0,
+ "mmlu_miscellaneous": 0.0,
+ "mmlu_moral_disputes": 0.0,
+ "mmlu_moral_scenarios": 0.0,
+ "mmlu_nutrition": 0.0,
+ "mmlu_other": "N/A",
+ "mmlu_philosophy": 0.0,
+ "mmlu_prehistory": 0.0,
+ "mmlu_professional_accounting": 0.0,
+ "mmlu_professional_law": 0.0,
+ "mmlu_professional_medicine": 0.0,
+ "mmlu_professional_psychology": 0.0,
+ "mmlu_public_relations": 0.0,
+ "mmlu_security_studies": 0.0,
+ "mmlu_social_sciences": "N/A",
+ "mmlu_sociology": 0.0,
+ "mmlu_stem": "N/A",
+ "mmlu_us_foreign_policy": 0.0,
+ "mmlu_virology": 0.0,
+ "mmlu_world_religions": 0.0,
+ "piqa": 1.0,
+ "pythia": "N/A",
+ "sciq": 1.0,
+ "wikitext": 2.0,
+ "winogrande": 1.0,
+ "wsc": 1.0
+ },
+ "n-shot": {
+ "ai2_arc": 0,
+ "arc_challenge": 0,
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diff --git a/lm-eval-output/aisingapore/sealion3b/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+{
+ "results": {
+ "truthfulqa": {
+ "acc,none": 0.29115457709716386,
+ "acc_stderr,none": 0.001635881417641523,
+ "bleu_max,none": 23.17592314469333,
+ "bleu_max_stderr,none": 0.7705199444430939,
+ "bleu_acc,none": 0.38310893512851896,
+ "bleu_acc_stderr,none": 0.017018461679389855,
+ "bleu_diff,none": 1.3638964471210027,
+ "bleu_diff_stderr,none": 0.8632433983524191,
+ "rouge1_max,none": 47.240232935223176,
+ "rouge1_max_stderr,none": 0.9284398908010626,
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+ "rouge1_acc_stderr,none": 0.016987039266142985,
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+ "rouge1_diff_stderr,none": 1.1718627062272666,
+ "rouge2_max,none": 32.053173111877065,
+ "rouge2_max_stderr,none": 1.0561632909441534,
+ "rouge2_acc,none": 0.3011015911872705,
+ "rouge2_acc_stderr,none": 0.016058999026100612,
+ "rouge2_diff,none": 1.5445848533033304,
+ "rouge2_diff_stderr,none": 1.2442679354094344,
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+ "rougeL_diff,none": 1.6657629586959137,
+ "rougeL_diff_stderr,none": 1.1786314310856658,
+ "alias": "truthfulqa"
+ },
+ "truthfulqa_gen": {
+ "bleu_max,none": 23.17592314469333,
+ "bleu_max_stderr,none": 0.7705199444430939,
+ "bleu_acc,none": 0.38310893512851896,
+ "bleu_acc_stderr,none": 0.017018461679389855,
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+ "rouge2_max,none": 32.053173111877065,
+ "rouge2_max_stderr,none": 1.0561632909441534,
+ "rouge2_acc,none": 0.3011015911872705,
+ "rouge2_acc_stderr,none": 0.016058999026100612,
+ "rouge2_diff,none": 1.5445848533033304,
+ "rouge2_diff_stderr,none": 1.2442679354094344,
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+ "rougeL_max_stderr,none": 0.9472465952140484,
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+ "rougeL_diff,none": 1.6657629586959137,
+ "rougeL_diff_stderr,none": 1.1786314310856658,
+ "alias": " - truthfulqa_gen"
+ },
+ "truthfulqa_mc1": {
+ "acc,none": 0.21542227662178703,
+ "acc_stderr,none": 0.014391902652427681,
+ "alias": " - truthfulqa_mc1"
+ },
+ "truthfulqa_mc2": {
+ "acc,none": 0.36688687757254074,
+ "acc_stderr,none": 0.01397983317212303,
+ "alias": " - truthfulqa_mc2"
+ }
+ },
+ "groups": {
+ "truthfulqa": {
+ "acc,none": 0.29115457709716386,
+ "acc_stderr,none": 0.001635881417641523,
+ "bleu_max,none": 23.17592314469333,
+ "bleu_max_stderr,none": 0.7705199444430939,
+ "bleu_acc,none": 0.38310893512851896,
+ "bleu_acc_stderr,none": 0.017018461679389855,
+ "bleu_diff,none": 1.3638964471210027,
+ "bleu_diff_stderr,none": 0.8632433983524191,
+ "rouge1_max,none": 47.240232935223176,
+ "rouge1_max_stderr,none": 0.9284398908010626,
+ "rouge1_acc,none": 0.379436964504284,
+ "rouge1_acc_stderr,none": 0.016987039266142985,
+ "rouge1_diff,none": 1.5514230336845742,
+ "rouge1_diff_stderr,none": 1.1718627062272666,
+ "rouge2_max,none": 32.053173111877065,
+ "rouge2_max_stderr,none": 1.0561632909441534,
+ "rouge2_acc,none": 0.3011015911872705,
+ "rouge2_acc_stderr,none": 0.016058999026100612,
+ "rouge2_diff,none": 1.5445848533033304,
+ "rouge2_diff_stderr,none": 1.2442679354094344,
+ "rougeL_max,none": 44.731411115557066,
+ "rougeL_max_stderr,none": 0.9472465952140484,
+ "rougeL_acc,none": 0.379436964504284,
+ "rougeL_acc_stderr,none": 0.01698703926614298,
+ "rougeL_diff,none": 1.6657629586959137,
+ "rougeL_diff_stderr,none": 1.1786314310856658,
+ "alias": "truthfulqa"
+ }
+ },
+ "configs": {
+ "truthfulqa_gen": {
+ "task": "truthfulqa_gen",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "generation",
+ "validation_split": "validation",
+ "process_docs": "def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset:\n return dataset.map(preprocess_function)\n",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
+ "doc_to_target": " ",
+ "process_results": "def process_results_gen(doc, results):\n completion = results[0]\n true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n all_refs = true_refs + false_refs\n\n # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n # # BLEURT\n # bleurt_scores_true = self.bleurt.compute(\n # predictions=[completion] * len(true_refs), references=true_refs\n # )[\"scores\"]\n # bleurt_scores_false = self.bleurt.compute(\n # predictions=[completion] * len(false_refs), references=false_refs\n # )[\"scores\"]\n # bleurt_correct = max(bleurt_scores_true)\n # bleurt_incorrect = max(bleurt_scores_false)\n # bleurt_max = bleurt_correct\n # bleurt_diff = bleurt_correct - bleurt_incorrect\n # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n # BLEU\n bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n bleu_max = bleu_correct\n bleu_diff = bleu_correct - bleu_incorrect\n bleu_acc = int(bleu_correct > bleu_incorrect)\n\n # ROUGE-N\n rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n # ROUGE-1\n rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n rouge1_max = rouge1_correct\n rouge1_diff = rouge1_correct - rouge1_incorrect\n rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n # ROUGE-2\n rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n rouge2_max = rouge2_correct\n rouge2_diff = rouge2_correct - rouge2_incorrect\n rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n # ROUGE-L\n rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n rougeL_max = rougeL_correct\n rougeL_diff = rougeL_correct - rougeL_incorrect\n rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n return {\n # \"bleurt_max\": bleurt_max,\n # \"bleurt_acc\": bleurt_acc,\n # \"bleurt_diff\": bleurt_diff,\n \"bleu_max\": bleu_max,\n \"bleu_acc\": bleu_acc,\n \"bleu_diff\": bleu_diff,\n \"rouge1_max\": rouge1_max,\n \"rouge1_acc\": rouge1_acc,\n \"rouge1_diff\": rouge1_diff,\n \"rouge2_max\": rouge2_max,\n \"rouge2_acc\": rouge2_acc,\n \"rouge2_diff\": rouge2_diff,\n \"rougeL_max\": rougeL_max,\n \"rougeL_acc\": rougeL_acc,\n \"rougeL_diff\": rougeL_diff,\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "bleu_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "generate_until",
+ "generation_kwargs": {
+ "until": [
+ "\n\n"
+ ],
+ "do_sample": false
+ },
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 3.0
+ }
+ },
+ "truthfulqa_mc1": {
+ "task": "truthfulqa_mc1",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc1_targets.choices}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "truthfulqa_mc2": {
+ "task": "truthfulqa_mc2",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc2_targets.choices}}",
+ "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "truthfulqa": "N/A",
+ "truthfulqa_gen": 3.0,
+ "truthfulqa_mc1": 2.0,
+ "truthfulqa_mc2": 2.0
+ },
+ "n-shot": {
+ "truthfulqa": 0,
+ "truthfulqa_gen": 0,
+ "truthfulqa_mc1": 0,
+ "truthfulqa_mc2": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion3b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 32
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/aisingapore/sealion3b/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
index 0000000000000000000000000000000000000000..006417523ed75042cd90080191416dca8c7b599a
--- /dev/null
+++ b/lm-eval-output/aisingapore/sealion3b/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+size 546052
diff --git a/lm-eval-output/aisingapore/sealion3b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..2059b8b2b7f7d1357f33a98022617af8bb593ac8
--- /dev/null
+++ b/lm-eval-output/aisingapore/sealion3b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,60 @@
+{
+ "results": {
+ "webqs": {
+ "exact_match,none": 0.0718503937007874,
+ "exact_match_stderr,none": 0.005730184515948714,
+ "alias": "webqs"
+ }
+ },
+ "configs": {
+ "webqs": {
+ "task": "webqs",
+ "group": [
+ "freebase"
+ ],
+ "dataset_path": "web_questions",
+ "training_split": "train",
+ "test_split": "test",
+ "doc_to_text": "Question: {{question}}\nAnswer:",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> List[int]:\n \"\"\"Return list of indices of accepted answers (all of them).\"\"\"\n remaining = _remove_prefixes(doc[\"answers\"])\n return list(range(len(remaining)))\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return all of the accepted answers as choices.\"\"\"\n return _remove_prefixes(doc[\"answers\"])\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "exact_match",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "webqs": 2.0
+ },
+ "n-shot": {
+ "webqs": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion3b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/aisingapore/sealion3b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
index 0000000000000000000000000000000000000000..04b63b2172791043ca6058506bb8c46da1588678
--- /dev/null
+++ b/lm-eval-output/aisingapore/sealion3b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+size 16466
diff --git a/lm-eval-output/aisingapore/sealion3b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ac803c598904d4489048d5404cead799ee6ee24
--- /dev/null
+++ b/lm-eval-output/aisingapore/sealion3b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,61 @@
+{
+ "results": {
+ "wic": {
+ "acc,none": 0.5,
+ "acc_stderr,none": 0.01981072129375818,
+ "alias": "wic"
+ }
+ },
+ "configs": {
+ "wic": {
+ "task": "wic",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wic",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Sentence 1: {{sentence1}}\nSentence 2: {{sentence2}}\nQuestion: Is the word '{{sentence1[start1:end1]}}' used in the same way in the two sentences above?\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "wic": 1.0
+ },
+ "n-shot": {
+ "wic": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion3b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
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+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/aisingapore/sealion3b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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@@ -0,0 +1,65 @@
+{
+ "results": {
+ "wikitext": {
+ "word_perplexity,none": 16.477546700595973,
+ "word_perplexity_stderr,none": "N/A",
+ "byte_perplexity,none": 1.6887485533398678,
+ "byte_perplexity_stderr,none": "N/A",
+ "bits_per_byte,none": 0.7559545336721784,
+ "bits_per_byte_stderr,none": "N/A",
+ "alias": "wikitext"
+ }
+ },
+ "configs": {
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
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+ "metric": "bits_per_byte"
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+ "output_type": "loglikelihood_rolling",
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+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "wikitext": 2.0
+ },
+ "n-shot": {
+ "wikitext": 0
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+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion3b,dtype=bfloat16,trust_remote_code=True",
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+ "batch_sizes": [],
+ "device": null,
+ "use_cache": null,
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diff --git a/lm-eval-output/aisingapore/sealion3b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+{
+ "results": {
+ "winogrande": {
+ "acc,none": 0.569060773480663,
+ "acc_stderr,none": 0.013917796623335968,
+ "alias": "winogrande"
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+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
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diff --git a/lm-eval-output/aisingapore/sealion3b/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/wnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/wnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "wnli"
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+ "configs": {
+ "wnli": {
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+ "group": "glue",
+ "dataset_path": "glue",
+ "dataset_name": "wnli",
+ "training_split": "train",
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+ "doc_to_text": "{{sentence1}}\nQuestion: {{sentence2}} True or False?\nAnswer:",
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+ "False",
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+ "metric": "acc"
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+ "should_decontaminate": false,
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+ "model": "hf",
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diff --git a/lm-eval-output/aisingapore/sealion3b/wnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/wnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/wsc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/wsc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+{
+ "results": {
+ "wsc": {
+ "acc,none": 0.36538461538461536,
+ "acc_stderr,none": 0.0474473339327792,
+ "alias": "wsc"
+ }
+ },
+ "configs": {
+ "wsc": {
+ "task": "wsc",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wsc.fixed",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n",
+ "doc_to_target": "label",
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diff --git a/lm-eval-output/aisingapore/sealion3b/wsc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/wsc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/wsc273/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/wsc273/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "acc,none": 0.6959706959706959,
+ "acc_stderr,none": 0.02789129939715294,
+ "alias": "wsc273"
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+ "configs": {
+ "wsc273": {
+ "task": "wsc273",
+ "dataset_path": "winograd_wsc",
+ "dataset_name": "wsc273",
+ "test_split": "test",
+ "process_docs": "def process_doc(dataset):\n def process_fn(doc):\n # The HF implementation of `wsc273` is not `partial evaluation` friendly.\n doc[\"text\"] = doc[\"text\"].replace(\" \", \" \")\n doc[\"options\"][0] = __normalize_option(doc, doc[\"options\"][0])\n doc[\"options\"][1] = __normalize_option(doc, doc[\"options\"][1])\n return doc\n\n return dataset.map(process_fn)\n",
+ "doc_to_text": "label",
+ "doc_to_target": "{% set index = pronoun_loc + pronoun | length %}{{text[index:]}}",
+ "doc_to_choice": "{% set template = text[:pronoun_loc] %}{{[template+options[0], template+options[1]]}}",
+ "description": "",
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+ "metric_list": [
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diff --git a/lm-eval-output/aisingapore/sealion3b/wsc273/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/wsc273/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "xcopa"
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+ "alias": " - xcopa_et"
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+ "alias": " - xcopa_ht"
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+ "alias": " - xcopa_id"
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+ "acc_stderr,none": 0.02237662679792717,
+ "alias": " - xcopa_it"
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+ "alias": " - xcopa_qu"
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+ "alias": " - xcopa_sw"
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+ "alias": " - xcopa_ta"
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+ "alias": " - xcopa_th"
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+ "xcopa_tr": {
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+ "alias": " - xcopa_tr"
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+ "acc_stderr,none": 0.02104961216613481,
+ "alias": " - xcopa_vi"
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+ "xcopa_zh": {
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+ "acc_stderr,none": 0.02185468495561126,
+ "alias": " - xcopa_zh"
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+ "acc_stderr,none": 0.05449048831875534,
+ "alias": "xcopa"
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+ "configs": {
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+ "task": "xcopa_et",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "et",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'sest', 'effect': 'seetõttu'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ht": {
+ "task": "xcopa_ht",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ht",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'poukisa', 'effect': 'donk sa'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_id": {
+ "task": "xcopa_id",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "id",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'karena', 'effect': 'maka'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_it": {
+ "task": "xcopa_it",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "it",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'perché', 'effect': 'quindi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_qu": {
+ "task": "xcopa_qu",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "qu",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'imataq', 'effect': 'chaymi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_sw": {
+ "task": "xcopa_sw",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "sw",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ta": {
+ "task": "xcopa_ta",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ta",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_th": {
+ "task": "xcopa_th",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "th",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_tr": {
+ "task": "xcopa_tr",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "tr",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
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+ "metric": "acc"
+ }
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_vi": {
+ "task": "xcopa_vi",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "vi",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
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+ "metric": "acc"
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ },
+ "xcopa_zh": {
+ "task": "xcopa_zh",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "zh",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': '因为', 'effect': '所以'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "xcopa": "N/A",
+ "xcopa_et": 1.0,
+ "xcopa_ht": 1.0,
+ "xcopa_id": 1.0,
+ "xcopa_it": 1.0,
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+ "xcopa_sw": 1.0,
+ "xcopa_ta": 1.0,
+ "xcopa_th": 1.0,
+ "xcopa_tr": 1.0,
+ "xcopa_vi": 1.0,
+ "xcopa_zh": 1.0
+ },
+ "n-shot": {
+ "xcopa": 0,
+ "xcopa_et": 0,
+ "xcopa_ht": 0,
+ "xcopa_id": 0,
+ "xcopa_it": 0,
+ "xcopa_qu": 0,
+ "xcopa_sw": 0,
+ "xcopa_ta": 0,
+ "xcopa_th": 0,
+ "xcopa_tr": 0,
+ "xcopa_vi": 0,
+ "xcopa_zh": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion3b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
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diff --git a/lm-eval-output/aisingapore/sealion3b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion3b/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": " - xnli_es"
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+ "alias": " - xnli_th"
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+ "alias": " - xnli_tr"
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+ "doc_to_text": "",
+ "doc_to_target": "label",
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+ "doc_to_text": "",
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+ "should_decontaminate": false,
+ "metadata": {
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diff --git a/lm-eval-output/aisingapore/sealion3b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion3b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion3b/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion7b/glue/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion7b/glue/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+}
\ No newline at end of file
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diff --git a/lm-eval-output/aisingapore/sealion7b/pythia/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion7b/pythia/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap": {
+ "task": "blimp_wh_vs_that_no_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap_long_distance": {
+ "task": "blimp_wh_vs_that_no_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap": {
+ "task": "blimp_wh_vs_that_with_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap_long_distance": {
+ "task": "blimp_wh_vs_that_with_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "lambada_openai": {
+ "task": "lambada_openai",
+ "group": [
+ "lambada"
+ ],
+ "dataset_path": "EleutherAI/lambada_openai",
+ "dataset_name": "default",
+ "test_split": "test",
+ "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+ "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "perplexity",
+ "aggregation": "perplexity",
+ "higher_is_better": false
+ },
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "loglikelihood",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{text}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "logiqa": {
+ "task": "logiqa",
+ "dataset_path": "EleutherAI/logiqa",
+ "dataset_name": "logiqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: \n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
+ "doc_to_target": "def doc_to_target(doc) -> int:\n choices = [\"a\", \"b\", \"c\", \"d\"]\n return choices.index(doc[\"label\"].strip())\n",
+ "doc_to_choice": "{{options}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{context}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "piqa": {
+ "task": "piqa",
+ "dataset_path": "piqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Question: {{goal}}\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[sol1, sol2]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "goal",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "sciq": {
+ "task": "sciq",
+ "dataset_path": "sciq",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
+ "doc_to_target": 3,
+ "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{support}} {{question}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "word_perplexity"
+ },
+ {
+ "metric": "byte_perplexity"
+ },
+ {
+ "metric": "bits_per_byte"
+ }
+ ],
+ "output_type": "loglikelihood_rolling",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wsc": {
+ "task": "wsc",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wsc.fixed",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "ai2_arc": "N/A",
+ "arc_challenge": 1.0,
+ "arc_easy": 1.0,
+ "blimp": "N/A",
+ "blimp_adjunct_island": 1.0,
+ "blimp_anaphor_gender_agreement": 1.0,
+ "blimp_anaphor_number_agreement": 1.0,
+ "blimp_animate_subject_passive": 1.0,
+ "blimp_animate_subject_trans": 1.0,
+ "blimp_causative": 1.0,
+ "blimp_complex_NP_island": 1.0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 1.0,
+ "blimp_coordinate_structure_constraint_object_extraction": 1.0,
+ "blimp_determiner_noun_agreement_1": 1.0,
+ "blimp_determiner_noun_agreement_2": 1.0,
+ "blimp_determiner_noun_agreement_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 1.0,
+ "blimp_distractor_agreement_relational_noun": 1.0,
+ "blimp_distractor_agreement_relative_clause": 1.0,
+ "blimp_drop_argument": 1.0,
+ "blimp_ellipsis_n_bar_1": 1.0,
+ "blimp_ellipsis_n_bar_2": 1.0,
+ "blimp_existential_there_object_raising": 1.0,
+ "blimp_existential_there_quantifiers_1": 1.0,
+ "blimp_existential_there_quantifiers_2": 1.0,
+ "blimp_existential_there_subject_raising": 1.0,
+ "blimp_expletive_it_object_raising": 1.0,
+ "blimp_inchoative": 1.0,
+ "blimp_intransitive": 1.0,
+ "blimp_irregular_past_participle_adjectives": 1.0,
+ "blimp_irregular_past_participle_verbs": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_left_branch_island_echo_question": 1.0,
+ "blimp_left_branch_island_simple_question": 1.0,
+ "blimp_matrix_question_npi_licensor_present": 1.0,
+ "blimp_npi_present_1": 1.0,
+ "blimp_npi_present_2": 1.0,
+ "blimp_only_npi_licensor_present": 1.0,
+ "blimp_only_npi_scope": 1.0,
+ "blimp_passive_1": 1.0,
+ "blimp_passive_2": 1.0,
+ "blimp_principle_A_c_command": 1.0,
+ "blimp_principle_A_case_1": 1.0,
+ "blimp_principle_A_case_2": 1.0,
+ "blimp_principle_A_domain_1": 1.0,
+ "blimp_principle_A_domain_2": 1.0,
+ "blimp_principle_A_domain_3": 1.0,
+ "blimp_principle_A_reconstruction": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_sentential_negation_npi_licensor_present": 1.0,
+ "blimp_sentential_negation_npi_scope": 1.0,
+ "blimp_sentential_subject_island": 1.0,
+ "blimp_superlative_quantifiers_1": 1.0,
+ "blimp_superlative_quantifiers_2": 1.0,
+ "blimp_tough_vs_raising_1": 1.0,
+ "blimp_tough_vs_raising_2": 1.0,
+ "blimp_transitive": 1.0,
+ "blimp_wh_island": 1.0,
+ "blimp_wh_questions_object_gap": 1.0,
+ "blimp_wh_questions_subject_gap": 1.0,
+ "blimp_wh_questions_subject_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_no_gap": 1.0,
+ "blimp_wh_vs_that_no_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_with_gap": 1.0,
+ "blimp_wh_vs_that_with_gap_long_distance": 1.0,
+ "lambada_openai": 1.0,
+ "logiqa": 1.0,
+ "mmlu": "N/A",
+ "mmlu_abstract_algebra": 0.0,
+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
+ "mmlu_college_computer_science": 0.0,
+ "mmlu_college_mathematics": 0.0,
+ "mmlu_college_medicine": 0.0,
+ "mmlu_college_physics": 0.0,
+ "mmlu_computer_security": 0.0,
+ "mmlu_conceptual_physics": 0.0,
+ "mmlu_econometrics": 0.0,
+ "mmlu_electrical_engineering": 0.0,
+ "mmlu_elementary_mathematics": 0.0,
+ "mmlu_formal_logic": 0.0,
+ "mmlu_global_facts": 0.0,
+ "mmlu_high_school_biology": 0.0,
+ "mmlu_high_school_chemistry": 0.0,
+ "mmlu_high_school_computer_science": 0.0,
+ "mmlu_high_school_european_history": 0.0,
+ "mmlu_high_school_geography": 0.0,
+ "mmlu_high_school_government_and_politics": 0.0,
+ "mmlu_high_school_macroeconomics": 0.0,
+ "mmlu_high_school_mathematics": 0.0,
+ "mmlu_high_school_microeconomics": 0.0,
+ "mmlu_high_school_physics": 0.0,
+ "mmlu_high_school_psychology": 0.0,
+ "mmlu_high_school_statistics": 0.0,
+ "mmlu_high_school_us_history": 0.0,
+ "mmlu_high_school_world_history": 0.0,
+ "mmlu_human_aging": 0.0,
+ "mmlu_human_sexuality": 0.0,
+ "mmlu_humanities": "N/A",
+ "mmlu_international_law": 0.0,
+ "mmlu_jurisprudence": 0.0,
+ "mmlu_logical_fallacies": 0.0,
+ "mmlu_machine_learning": 0.0,
+ "mmlu_management": 0.0,
+ "mmlu_marketing": 0.0,
+ "mmlu_medical_genetics": 0.0,
+ "mmlu_miscellaneous": 0.0,
+ "mmlu_moral_disputes": 0.0,
+ "mmlu_moral_scenarios": 0.0,
+ "mmlu_nutrition": 0.0,
+ "mmlu_other": "N/A",
+ "mmlu_philosophy": 0.0,
+ "mmlu_prehistory": 0.0,
+ "mmlu_professional_accounting": 0.0,
+ "mmlu_professional_law": 0.0,
+ "mmlu_professional_medicine": 0.0,
+ "mmlu_professional_psychology": 0.0,
+ "mmlu_public_relations": 0.0,
+ "mmlu_security_studies": 0.0,
+ "mmlu_social_sciences": "N/A",
+ "mmlu_sociology": 0.0,
+ "mmlu_stem": "N/A",
+ "mmlu_us_foreign_policy": 0.0,
+ "mmlu_virology": 0.0,
+ "mmlu_world_religions": 0.0,
+ "piqa": 1.0,
+ "pythia": "N/A",
+ "sciq": 1.0,
+ "wikitext": 2.0,
+ "winogrande": 1.0,
+ "wsc": 1.0
+ },
+ "n-shot": {
+ "ai2_arc": 0,
+ "arc_challenge": 0,
+ "arc_easy": 0,
+ "blimp": 0,
+ "blimp_adjunct_island": 0,
+ "blimp_anaphor_gender_agreement": 0,
+ "blimp_anaphor_number_agreement": 0,
+ "blimp_animate_subject_passive": 0,
+ "blimp_animate_subject_trans": 0,
+ "blimp_causative": 0,
+ "blimp_complex_NP_island": 0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 0,
+ "blimp_coordinate_structure_constraint_object_extraction": 0,
+ "blimp_determiner_noun_agreement_1": 0,
+ "blimp_determiner_noun_agreement_2": 0,
+ "blimp_determiner_noun_agreement_irregular_1": 0,
+ "blimp_determiner_noun_agreement_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 0,
+ "blimp_distractor_agreement_relational_noun": 0,
+ "blimp_distractor_agreement_relative_clause": 0,
+ "blimp_drop_argument": 0,
+ "blimp_ellipsis_n_bar_1": 0,
+ "blimp_ellipsis_n_bar_2": 0,
+ "blimp_existential_there_object_raising": 0,
+ "blimp_existential_there_quantifiers_1": 0,
+ "blimp_existential_there_quantifiers_2": 0,
+ "blimp_existential_there_subject_raising": 0,
+ "blimp_expletive_it_object_raising": 0,
+ "blimp_inchoative": 0,
+ "blimp_intransitive": 0,
+ "blimp_irregular_past_participle_adjectives": 0,
+ "blimp_irregular_past_participle_verbs": 0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 0,
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+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
+ "doc_to_target": " ",
+ "process_results": "def process_results_gen(doc, results):\n completion = results[0]\n true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n all_refs = true_refs + false_refs\n\n # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n # # BLEURT\n # bleurt_scores_true = self.bleurt.compute(\n # predictions=[completion] * len(true_refs), references=true_refs\n # )[\"scores\"]\n # bleurt_scores_false = self.bleurt.compute(\n # predictions=[completion] * len(false_refs), references=false_refs\n # )[\"scores\"]\n # bleurt_correct = max(bleurt_scores_true)\n # bleurt_incorrect = max(bleurt_scores_false)\n # bleurt_max = bleurt_correct\n # bleurt_diff = bleurt_correct - bleurt_incorrect\n # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n # BLEU\n bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n bleu_max = bleu_correct\n bleu_diff = bleu_correct - bleu_incorrect\n bleu_acc = int(bleu_correct > bleu_incorrect)\n\n # ROUGE-N\n rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n # ROUGE-1\n rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n rouge1_max = rouge1_correct\n rouge1_diff = rouge1_correct - rouge1_incorrect\n rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n # ROUGE-2\n rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n rouge2_max = rouge2_correct\n rouge2_diff = rouge2_correct - rouge2_incorrect\n rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n # ROUGE-L\n rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n rougeL_max = rougeL_correct\n rougeL_diff = rougeL_correct - rougeL_incorrect\n rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n return {\n # \"bleurt_max\": bleurt_max,\n # \"bleurt_acc\": bleurt_acc,\n # \"bleurt_diff\": bleurt_diff,\n \"bleu_max\": bleu_max,\n \"bleu_acc\": bleu_acc,\n \"bleu_diff\": bleu_diff,\n \"rouge1_max\": rouge1_max,\n \"rouge1_acc\": rouge1_acc,\n \"rouge1_diff\": rouge1_diff,\n \"rouge2_max\": rouge2_max,\n \"rouge2_acc\": rouge2_acc,\n \"rouge2_diff\": rouge2_diff,\n \"rougeL_max\": rougeL_max,\n \"rougeL_acc\": rougeL_acc,\n \"rougeL_diff\": rougeL_diff,\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "bleu_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "generate_until",
+ "generation_kwargs": {
+ "until": [
+ "\n\n"
+ ],
+ "do_sample": false
+ },
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 3.0
+ }
+ },
+ "truthfulqa_mc1": {
+ "task": "truthfulqa_mc1",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc1_targets.choices}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "truthfulqa_mc2": {
+ "task": "truthfulqa_mc2",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc2_targets.choices}}",
+ "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "truthfulqa": "N/A",
+ "truthfulqa_gen": 3.0,
+ "truthfulqa_mc1": 2.0,
+ "truthfulqa_mc2": 2.0
+ },
+ "n-shot": {
+ "truthfulqa": 0,
+ "truthfulqa_gen": 0,
+ "truthfulqa_mc1": 0,
+ "truthfulqa_mc2": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion7b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 16
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/aisingapore/sealion7b/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion7b/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+size 551447
diff --git a/lm-eval-output/aisingapore/sealion7b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion7b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..f98083ac4483023f5bf0d533fd56a6953e74522f
--- /dev/null
+++ b/lm-eval-output/aisingapore/sealion7b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,60 @@
+{
+ "results": {
+ "webqs": {
+ "exact_match,none": 0.029035433070866142,
+ "exact_match_stderr,none": 0.003725725747722712,
+ "alias": "webqs"
+ }
+ },
+ "configs": {
+ "webqs": {
+ "task": "webqs",
+ "group": [
+ "freebase"
+ ],
+ "dataset_path": "web_questions",
+ "training_split": "train",
+ "test_split": "test",
+ "doc_to_text": "Question: {{question}}\nAnswer:",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> List[int]:\n \"\"\"Return list of indices of accepted answers (all of them).\"\"\"\n remaining = _remove_prefixes(doc[\"answers\"])\n return list(range(len(remaining)))\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return all of the accepted answers as choices.\"\"\"\n return _remove_prefixes(doc[\"answers\"])\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "exact_match",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "webqs": 2.0
+ },
+ "n-shot": {
+ "webqs": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion7b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/aisingapore/sealion7b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion7b/webqs/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+size 19140
diff --git a/lm-eval-output/aisingapore/sealion7b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion7b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..947cfd7ba5bf05aa130cca55dd46e7739603a754
--- /dev/null
+++ b/lm-eval-output/aisingapore/sealion7b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,61 @@
+{
+ "results": {
+ "wic": {
+ "acc,none": 0.5,
+ "acc_stderr,none": 0.01981072129375818,
+ "alias": "wic"
+ }
+ },
+ "configs": {
+ "wic": {
+ "task": "wic",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wic",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Sentence 1: {{sentence1}}\nSentence 2: {{sentence2}}\nQuestion: Is the word '{{sentence1[start1:end1]}}' used in the same way in the two sentences above?\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "wic": 1.0
+ },
+ "n-shot": {
+ "wic": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion7b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/aisingapore/sealion7b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion7b/wic/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+size 17695
diff --git a/lm-eval-output/aisingapore/sealion7b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion7b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..942fa43a39e03db2da9339a7824526eaf8f42f33
--- /dev/null
+++ b/lm-eval-output/aisingapore/sealion7b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,65 @@
+{
+ "results": {
+ "wikitext": {
+ "word_perplexity,none": 13.958385271895754,
+ "word_perplexity_stderr,none": "N/A",
+ "byte_perplexity,none": 1.6371553876002254,
+ "byte_perplexity_stderr,none": "N/A",
+ "bits_per_byte,none": 0.7111912590639013,
+ "bits_per_byte_stderr,none": "N/A",
+ "alias": "wikitext"
+ }
+ },
+ "configs": {
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "word_perplexity"
+ },
+ {
+ "metric": "byte_perplexity"
+ },
+ {
+ "metric": "bits_per_byte"
+ }
+ ],
+ "output_type": "loglikelihood_rolling",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "wikitext": 2.0
+ },
+ "n-shot": {
+ "wikitext": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=aisingapore/sealion7b,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/aisingapore/sealion7b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/aisingapore/sealion7b/wikitext/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/aisingapore/sealion7b/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/aisingapore/sealion7b/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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index 0000000000000000000000000000000000000000..d160206069e28a41a8d734e3084906a81ca84ce4
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@@ -0,0 +1,58 @@
+{
+ "results": {
+ "winogrande": {
+ "acc,none": 0.6022099447513812,
+ "acc_stderr,none": 0.01375574351374902,
+ "alias": "winogrande"
+ }
+ },
+ "configs": {
+ "winogrande": {
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+ "doc_to_choice": [
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+ "description": "以下是关于农学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
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+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "description": "以下是关于解剖学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "dataset_name": "ancient_chinese",
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+ "doc_to_choice": [
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+ "C",
+ "D"
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+ "description": "以下是关于古汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
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+ "doc_to_choice": [
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+ "D"
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+ "description": "以下是关于艺术学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "dataset_name": "astronomy",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "C",
+ "D"
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+ "description": "以下是关于天文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "output_type": "multiple_choice",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
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+ "description": "以下是关于商业伦理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metric_list": [
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+ "description": "以下是关于中国公务员考试的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国驾驶规则的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_food_culture": {
+ "task": "cmmlu_chinese_food_culture",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_food_culture",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国饮食文化的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_foreign_policy": {
+ "task": "cmmlu_chinese_foreign_policy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国外交政策的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_history": {
+ "task": "cmmlu_chinese_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_literature": {
+ "task": "cmmlu_chinese_literature",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_literature",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_teacher_qualification": {
+ "task": "cmmlu_chinese_teacher_qualification",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_teacher_qualification",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国教师资格的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_clinical_knowledge": {
+ "task": "cmmlu_clinical_knowledge",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于临床知识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_actuarial_science": {
+ "task": "cmmlu_college_actuarial_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_actuarial_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学精算学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_education": {
+ "task": "cmmlu_college_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_engineering_hydrology": {
+ "task": "cmmlu_college_engineering_hydrology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_engineering_hydrology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学工程水文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_law": {
+ "task": "cmmlu_college_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学法律的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_mathematics": {
+ "task": "cmmlu_college_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medical_statistics": {
+ "task": "cmmlu_college_medical_statistics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medical_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学统计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medicine": {
+ "task": "cmmlu_college_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_science": {
+ "task": "cmmlu_computer_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_security": {
+ "task": "cmmlu_computer_security",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机安全的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_conceptual_physics": {
+ "task": "cmmlu_conceptual_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于概念物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_construction_project_management": {
+ "task": "cmmlu_construction_project_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "construction_project_management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于建设工程管理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_economics": {
+ "task": "cmmlu_economics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "economics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于经济学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_education": {
+ "task": "cmmlu_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_electrical_engineering": {
+ "task": "cmmlu_electrical_engineering",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于电气工程的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_chinese": {
+ "task": "cmmlu_elementary_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学语文的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_commonsense": {
+ "task": "cmmlu_elementary_commonsense",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_commonsense",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学常识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_information_and_technology": {
+ "task": "cmmlu_elementary_information_and_technology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_information_and_technology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学信息技术的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_mathematics": {
+ "task": "cmmlu_elementary_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于初等数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_ethnology": {
+ "task": "cmmlu_ethnology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "ethnology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于民族学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_food_science": {
+ "task": "cmmlu_food_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "food_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于食品科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_genetics": {
+ "task": "cmmlu_genetics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于遗传学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_global_facts": {
+ "task": "cmmlu_global_facts",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于全球事实的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_biology": {
+ "task": "cmmlu_high_school_biology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中生物的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_chemistry": {
+ "task": "cmmlu_high_school_chemistry",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中化学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_geography": {
+ "task": "cmmlu_high_school_geography",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中地理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_mathematics": {
+ "task": "cmmlu_high_school_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_physics": {
+ "task": "cmmlu_high_school_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_politics": {
+ "task": "cmmlu_high_school_politics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中政治的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_human_sexuality": {
+ "task": "cmmlu_human_sexuality",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于人类性行为的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_international_law": {
+ "task": "cmmlu_international_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于国际法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_journalism": {
+ "task": "cmmlu_journalism",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "journalism",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于新闻学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_jurisprudence": {
+ "task": "cmmlu_jurisprudence",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_legal_and_moral_basis": {
+ "task": "cmmlu_legal_and_moral_basis",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "legal_and_moral_basis",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法律与道德基础的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_logical": {
+ "task": "cmmlu_logical",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "logical",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于逻辑学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_machine_learning": {
+ "task": "cmmlu_machine_learning",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于机器学习的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_management": {
+ "task": "cmmlu_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于管理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marketing": {
+ "task": "cmmlu_marketing",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于市场营销的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marxist_theory": {
+ "task": "cmmlu_marxist_theory",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marxist_theory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于马克思主义理论的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_modern_chinese": {
+ "task": "cmmlu_modern_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "modern_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于现代汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_nutrition": {
+ "task": "cmmlu_nutrition",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于营养学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_philosophy": {
+ "task": "cmmlu_philosophy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于哲学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_accounting": {
+ "task": "cmmlu_professional_accounting",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业会计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_law": {
+ "task": "cmmlu_professional_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_medicine": {
+ "task": "cmmlu_professional_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_psychology": {
+ "task": "cmmlu_professional_psychology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业心理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_public_relations": {
+ "task": "cmmlu_public_relations",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于公共关系的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_security_study": {
+ "task": "cmmlu_security_study",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "security_study",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于安全研究的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sociology": {
+ "task": "cmmlu_sociology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于社会学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sports_science": {
+ "task": "cmmlu_sports_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sports_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于体育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_traditional_chinese_medicine": {
+ "task": "cmmlu_traditional_chinese_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "traditional_chinese_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中医中药的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_virology": {
+ "task": "cmmlu_virology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于病毒学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_world_history": {
+ "task": "cmmlu_world_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_world_religions": {
+ "task": "cmmlu_world_religions",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界宗教的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ }
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+ "alias": "copa"
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+ "should_decontaminate": false,
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+ },
+ "mmlu_computer_security": {
+ "alias": " - computer_security",
+ "acc,none": 0.36,
+ "acc_stderr,none": 0.04824181513244218
+ },
+ "mmlu_conceptual_physics": {
+ "alias": " - conceptual_physics",
+ "acc,none": 0.30638297872340425,
+ "acc_stderr,none": 0.030135906478517563
+ },
+ "mmlu_electrical_engineering": {
+ "alias": " - electrical_engineering",
+ "acc,none": 0.27586206896551724,
+ "acc_stderr,none": 0.037245636197746325
+ },
+ "mmlu_elementary_mathematics": {
+ "alias": " - elementary_mathematics",
+ "acc,none": 0.22486772486772486,
+ "acc_stderr,none": 0.02150209607822914
+ },
+ "mmlu_high_school_biology": {
+ "alias": " - high_school_biology",
+ "acc,none": 0.3548387096774194,
+ "acc_stderr,none": 0.027218889773308767
+ },
+ "mmlu_high_school_chemistry": {
+ "alias": " - high_school_chemistry",
+ "acc,none": 0.28078817733990147,
+ "acc_stderr,none": 0.0316185633535861
+ },
+ "mmlu_high_school_computer_science": {
+ "alias": " - high_school_computer_science",
+ "acc,none": 0.3,
+ "acc_stderr,none": 0.046056618647183814
+ },
+ "mmlu_high_school_mathematics": {
+ "alias": " - high_school_mathematics",
+ "acc,none": 0.24074074074074073,
+ "acc_stderr,none": 0.02606715922227581
+ },
+ "mmlu_high_school_physics": {
+ "alias": " - high_school_physics",
+ "acc,none": 0.23178807947019867,
+ "acc_stderr,none": 0.034454062719870546
+ },
+ "mmlu_high_school_statistics": {
+ "alias": " - high_school_statistics",
+ "acc,none": 0.1574074074074074,
+ "acc_stderr,none": 0.02483717351824239
+ },
+ "mmlu_machine_learning": {
+ "alias": " - machine_learning",
+ "acc,none": 0.30357142857142855,
+ "acc_stderr,none": 0.04364226155841044
+ }
+ },
+ "groups": {
+ "mmlu": {
+ "acc,none": 0.3146275459336277,
+ "acc_stderr,none": 0.05880633606239949,
+ "alias": "mmlu"
+ },
+ "mmlu_humanities": {
+ "alias": " - humanities",
+ "acc,none": 0.30393198724760895,
+ "acc_stderr,none": 0.0534364834943281
+ },
+ "mmlu_other": {
+ "alias": " - other",
+ "acc,none": 0.3646604441583521,
+ "acc_stderr,none": 0.047703931866617054
+ },
+ "mmlu_social_sciences": {
+ "alias": " - social_sciences",
+ "acc,none": 0.3262918427039324,
+ "acc_stderr,none": 0.05747959044146185
+ },
+ "mmlu_stem": {
+ "alias": " - stem",
+ "acc,none": 0.26990168093878847,
+ "acc_stderr,none": 0.05521336680026564
+ }
+ },
+ "configs": {
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
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+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "higher_is_better": true
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+ "should_decontaminate": false,
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+ "blimp_wh_vs_that_no_gap": {
+ "task": "blimp_wh_vs_that_no_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap_long_distance": {
+ "task": "blimp_wh_vs_that_no_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap": {
+ "task": "blimp_wh_vs_that_with_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap_long_distance": {
+ "task": "blimp_wh_vs_that_with_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "lambada_openai": {
+ "task": "lambada_openai",
+ "group": [
+ "lambada"
+ ],
+ "dataset_path": "EleutherAI/lambada_openai",
+ "dataset_name": "default",
+ "test_split": "test",
+ "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+ "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "perplexity",
+ "aggregation": "perplexity",
+ "higher_is_better": false
+ },
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "loglikelihood",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{text}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "logiqa": {
+ "task": "logiqa",
+ "dataset_path": "EleutherAI/logiqa",
+ "dataset_name": "logiqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: \n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
+ "doc_to_target": "def doc_to_target(doc) -> int:\n choices = [\"a\", \"b\", \"c\", \"d\"]\n return choices.index(doc[\"label\"].strip())\n",
+ "doc_to_choice": "{{options}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{context}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "piqa": {
+ "task": "piqa",
+ "dataset_path": "piqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Question: {{goal}}\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[sol1, sol2]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "goal",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "sciq": {
+ "task": "sciq",
+ "dataset_path": "sciq",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
+ "doc_to_target": 3,
+ "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{support}} {{question}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "word_perplexity"
+ },
+ {
+ "metric": "byte_perplexity"
+ },
+ {
+ "metric": "bits_per_byte"
+ }
+ ],
+ "output_type": "loglikelihood_rolling",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wsc": {
+ "task": "wsc",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wsc.fixed",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "ai2_arc": "N/A",
+ "arc_challenge": 1.0,
+ "arc_easy": 1.0,
+ "blimp": "N/A",
+ "blimp_adjunct_island": 1.0,
+ "blimp_anaphor_gender_agreement": 1.0,
+ "blimp_anaphor_number_agreement": 1.0,
+ "blimp_animate_subject_passive": 1.0,
+ "blimp_animate_subject_trans": 1.0,
+ "blimp_causative": 1.0,
+ "blimp_complex_NP_island": 1.0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 1.0,
+ "blimp_coordinate_structure_constraint_object_extraction": 1.0,
+ "blimp_determiner_noun_agreement_1": 1.0,
+ "blimp_determiner_noun_agreement_2": 1.0,
+ "blimp_determiner_noun_agreement_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 1.0,
+ "blimp_distractor_agreement_relational_noun": 1.0,
+ "blimp_distractor_agreement_relative_clause": 1.0,
+ "blimp_drop_argument": 1.0,
+ "blimp_ellipsis_n_bar_1": 1.0,
+ "blimp_ellipsis_n_bar_2": 1.0,
+ "blimp_existential_there_object_raising": 1.0,
+ "blimp_existential_there_quantifiers_1": 1.0,
+ "blimp_existential_there_quantifiers_2": 1.0,
+ "blimp_existential_there_subject_raising": 1.0,
+ "blimp_expletive_it_object_raising": 1.0,
+ "blimp_inchoative": 1.0,
+ "blimp_intransitive": 1.0,
+ "blimp_irregular_past_participle_adjectives": 1.0,
+ "blimp_irregular_past_participle_verbs": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_left_branch_island_echo_question": 1.0,
+ "blimp_left_branch_island_simple_question": 1.0,
+ "blimp_matrix_question_npi_licensor_present": 1.0,
+ "blimp_npi_present_1": 1.0,
+ "blimp_npi_present_2": 1.0,
+ "blimp_only_npi_licensor_present": 1.0,
+ "blimp_only_npi_scope": 1.0,
+ "blimp_passive_1": 1.0,
+ "blimp_passive_2": 1.0,
+ "blimp_principle_A_c_command": 1.0,
+ "blimp_principle_A_case_1": 1.0,
+ "blimp_principle_A_case_2": 1.0,
+ "blimp_principle_A_domain_1": 1.0,
+ "blimp_principle_A_domain_2": 1.0,
+ "blimp_principle_A_domain_3": 1.0,
+ "blimp_principle_A_reconstruction": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_sentential_negation_npi_licensor_present": 1.0,
+ "blimp_sentential_negation_npi_scope": 1.0,
+ "blimp_sentential_subject_island": 1.0,
+ "blimp_superlative_quantifiers_1": 1.0,
+ "blimp_superlative_quantifiers_2": 1.0,
+ "blimp_tough_vs_raising_1": 1.0,
+ "blimp_tough_vs_raising_2": 1.0,
+ "blimp_transitive": 1.0,
+ "blimp_wh_island": 1.0,
+ "blimp_wh_questions_object_gap": 1.0,
+ "blimp_wh_questions_subject_gap": 1.0,
+ "blimp_wh_questions_subject_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_no_gap": 1.0,
+ "blimp_wh_vs_that_no_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_with_gap": 1.0,
+ "blimp_wh_vs_that_with_gap_long_distance": 1.0,
+ "lambada_openai": 1.0,
+ "logiqa": 1.0,
+ "mmlu": "N/A",
+ "mmlu_abstract_algebra": 0.0,
+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
+ "mmlu_college_computer_science": 0.0,
+ "mmlu_college_mathematics": 0.0,
+ "mmlu_college_medicine": 0.0,
+ "mmlu_college_physics": 0.0,
+ "mmlu_computer_security": 0.0,
+ "mmlu_conceptual_physics": 0.0,
+ "mmlu_econometrics": 0.0,
+ "mmlu_electrical_engineering": 0.0,
+ "mmlu_elementary_mathematics": 0.0,
+ "mmlu_formal_logic": 0.0,
+ "mmlu_global_facts": 0.0,
+ "mmlu_high_school_biology": 0.0,
+ "mmlu_high_school_chemistry": 0.0,
+ "mmlu_high_school_computer_science": 0.0,
+ "mmlu_high_school_european_history": 0.0,
+ "mmlu_high_school_geography": 0.0,
+ "mmlu_high_school_government_and_politics": 0.0,
+ "mmlu_high_school_macroeconomics": 0.0,
+ "mmlu_high_school_mathematics": 0.0,
+ "mmlu_high_school_microeconomics": 0.0,
+ "mmlu_high_school_physics": 0.0,
+ "mmlu_high_school_psychology": 0.0,
+ "mmlu_high_school_statistics": 0.0,
+ "mmlu_high_school_us_history": 0.0,
+ "mmlu_high_school_world_history": 0.0,
+ "mmlu_human_aging": 0.0,
+ "mmlu_human_sexuality": 0.0,
+ "mmlu_humanities": "N/A",
+ "mmlu_international_law": 0.0,
+ "mmlu_jurisprudence": 0.0,
+ "mmlu_logical_fallacies": 0.0,
+ "mmlu_machine_learning": 0.0,
+ "mmlu_management": 0.0,
+ "mmlu_marketing": 0.0,
+ "mmlu_medical_genetics": 0.0,
+ "mmlu_miscellaneous": 0.0,
+ "mmlu_moral_disputes": 0.0,
+ "mmlu_moral_scenarios": 0.0,
+ "mmlu_nutrition": 0.0,
+ "mmlu_other": "N/A",
+ "mmlu_philosophy": 0.0,
+ "mmlu_prehistory": 0.0,
+ "mmlu_professional_accounting": 0.0,
+ "mmlu_professional_law": 0.0,
+ "mmlu_professional_medicine": 0.0,
+ "mmlu_professional_psychology": 0.0,
+ "mmlu_public_relations": 0.0,
+ "mmlu_security_studies": 0.0,
+ "mmlu_social_sciences": "N/A",
+ "mmlu_sociology": 0.0,
+ "mmlu_stem": "N/A",
+ "mmlu_us_foreign_policy": 0.0,
+ "mmlu_virology": 0.0,
+ "mmlu_world_religions": 0.0,
+ "piqa": 1.0,
+ "pythia": "N/A",
+ "sciq": 1.0,
+ "wikitext": 2.0,
+ "winogrande": 1.0,
+ "wsc": 1.0
+ },
+ "n-shot": {
+ "ai2_arc": 0,
+ "arc_challenge": 0,
+ "arc_easy": 0,
+ "blimp": 0,
+ "blimp_adjunct_island": 0,
+ "blimp_anaphor_gender_agreement": 0,
+ "blimp_anaphor_number_agreement": 0,
+ "blimp_animate_subject_passive": 0,
+ "blimp_animate_subject_trans": 0,
+ "blimp_causative": 0,
+ "blimp_complex_NP_island": 0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 0,
+ "blimp_coordinate_structure_constraint_object_extraction": 0,
+ "blimp_determiner_noun_agreement_1": 0,
+ "blimp_determiner_noun_agreement_2": 0,
+ "blimp_determiner_noun_agreement_irregular_1": 0,
+ "blimp_determiner_noun_agreement_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 0,
+ "blimp_distractor_agreement_relational_noun": 0,
+ "blimp_distractor_agreement_relative_clause": 0,
+ "blimp_drop_argument": 0,
+ "blimp_ellipsis_n_bar_1": 0,
+ "blimp_ellipsis_n_bar_2": 0,
+ "blimp_existential_there_object_raising": 0,
+ "blimp_existential_there_quantifiers_1": 0,
+ "blimp_existential_there_quantifiers_2": 0,
+ "blimp_existential_there_subject_raising": 0,
+ "blimp_expletive_it_object_raising": 0,
+ "blimp_inchoative": 0,
+ "blimp_intransitive": 0,
+ "blimp_irregular_past_participle_adjectives": 0,
+ "blimp_irregular_past_participle_verbs": 0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 0,
+ "blimp_left_branch_island_echo_question": 0,
+ "blimp_left_branch_island_simple_question": 0,
+ "blimp_matrix_question_npi_licensor_present": 0,
+ "blimp_npi_present_1": 0,
+ "blimp_npi_present_2": 0,
+ "blimp_only_npi_licensor_present": 0,
+ "blimp_only_npi_scope": 0,
+ "blimp_passive_1": 0,
+ "blimp_passive_2": 0,
+ "blimp_principle_A_c_command": 0,
+ "blimp_principle_A_case_1": 0,
+ "blimp_principle_A_case_2": 0,
+ "blimp_principle_A_domain_1": 0,
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+ "blimp_principle_A_domain_3": 0,
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+ "em,none": 0.2701,
+ "em_stderr,none": 0.004440334520851811,
+ "alias": "record"
+ }
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+ "record": {
+ "task": "record",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "record",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n initial_text, *highlights = doc[\"passage\"].strip().split(\"\\n@highlight\\n\")\n text = initial_text + \"\\n\\n\"\n for highlight in highlights:\n text += f\" - {highlight}.\\n\"\n return text\n",
+ "doc_to_target": "{{answers}}",
+ "doc_to_choice": "{{entities}}",
+ "process_results": "def process_results(doc, results):\n # ReCoRD's evaluation is actually deceptively simple:\n # - Pick the maximum likelihood prediction entity\n # - Evaluate the accuracy and token F1 PER EXAMPLE\n # - Average over all examples\n max_idx = np.argmax(np.array([result[0] for result in results]))\n\n prediction = doc[\"entities\"][max_idx]\n gold_label_set = doc[\"answers\"]\n f1 = metric_max_over_ground_truths(\n squad_metrics.compute_f1, prediction, gold_label_set\n )\n em = metric_max_over_ground_truths(\n squad_metrics.compute_exact, prediction, gold_label_set\n )\n\n return {\n \"f1\": f1,\n \"em\": em,\n }\n",
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+ ],
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+ "version": 1.0
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+ }
+ },
+ "versions": {
+ "sciq": 1.0
+ },
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+ "bleu_max_stderr,none": 0.8210922632451596,
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+ "rougeL_diff_stderr,none": 0.9750861508263083,
+ "alias": "truthfulqa"
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+ "rougeL_diff,none": -10.37795626225276,
+ "rougeL_diff_stderr,none": 0.9750861508263083,
+ "alias": " - truthfulqa_gen"
+ },
+ "truthfulqa_mc1": {
+ "acc,none": 0.24724602203182375,
+ "acc_stderr,none": 0.015102404797359652,
+ "alias": " - truthfulqa_mc1"
+ },
+ "truthfulqa_mc2": {
+ "acc,none": 0.3901033527944892,
+ "acc_stderr,none": 0.013871394609417833,
+ "alias": " - truthfulqa_mc2"
+ }
+ },
+ "groups": {
+ "truthfulqa": {
+ "acc,none": 0.31867468741315647,
+ "acc_stderr,none": 0.0014864150049306065,
+ "bleu_max,none": 27.361223632558687,
+ "bleu_max_stderr,none": 0.8210922632451596,
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+ "rougeL_diff,none": -10.37795626225276,
+ "rougeL_diff_stderr,none": 0.9750861508263083,
+ "alias": "truthfulqa"
+ }
+ },
+ "configs": {
+ "truthfulqa_gen": {
+ "task": "truthfulqa_gen",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "generation",
+ "validation_split": "validation",
+ "process_docs": "def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset:\n return dataset.map(preprocess_function)\n",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
+ "doc_to_target": " ",
+ "process_results": "def process_results_gen(doc, results):\n completion = results[0]\n true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n all_refs = true_refs + false_refs\n\n # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n # # BLEURT\n # bleurt_scores_true = self.bleurt.compute(\n # predictions=[completion] * len(true_refs), references=true_refs\n # )[\"scores\"]\n # bleurt_scores_false = self.bleurt.compute(\n # predictions=[completion] * len(false_refs), references=false_refs\n # )[\"scores\"]\n # bleurt_correct = max(bleurt_scores_true)\n # bleurt_incorrect = max(bleurt_scores_false)\n # bleurt_max = bleurt_correct\n # bleurt_diff = bleurt_correct - bleurt_incorrect\n # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n # BLEU\n bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n bleu_max = bleu_correct\n bleu_diff = bleu_correct - bleu_incorrect\n bleu_acc = int(bleu_correct > bleu_incorrect)\n\n # ROUGE-N\n rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n # ROUGE-1\n rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n rouge1_max = rouge1_correct\n rouge1_diff = rouge1_correct - rouge1_incorrect\n rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n # ROUGE-2\n rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n rouge2_max = rouge2_correct\n rouge2_diff = rouge2_correct - rouge2_incorrect\n rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n # ROUGE-L\n rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n rougeL_max = rougeL_correct\n rougeL_diff = rougeL_correct - rougeL_incorrect\n rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n return {\n # \"bleurt_max\": bleurt_max,\n # \"bleurt_acc\": bleurt_acc,\n # \"bleurt_diff\": bleurt_diff,\n \"bleu_max\": bleu_max,\n \"bleu_acc\": bleu_acc,\n \"bleu_diff\": bleu_diff,\n \"rouge1_max\": rouge1_max,\n \"rouge1_acc\": rouge1_acc,\n \"rouge1_diff\": rouge1_diff,\n \"rouge2_max\": rouge2_max,\n \"rouge2_acc\": rouge2_acc,\n \"rouge2_diff\": rouge2_diff,\n \"rougeL_max\": rougeL_max,\n \"rougeL_acc\": rougeL_acc,\n \"rougeL_diff\": rougeL_diff,\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "bleu_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "generate_until",
+ "generation_kwargs": {
+ "until": [
+ "\n\n"
+ ],
+ "do_sample": false
+ },
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 3.0
+ }
+ },
+ "truthfulqa_mc1": {
+ "task": "truthfulqa_mc1",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc1_targets.choices}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "truthfulqa_mc2": {
+ "task": "truthfulqa_mc2",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc2_targets.choices}}",
+ "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "truthfulqa": "N/A",
+ "truthfulqa_gen": 3.0,
+ "truthfulqa_mc1": 2.0,
+ "truthfulqa_mc2": 2.0
+ },
+ "n-shot": {
+ "truthfulqa": 0,
+ "truthfulqa_gen": 0,
+ "truthfulqa_mc1": 0,
+ "truthfulqa_mc2": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7791116aa1439f63dc58b976f2893963e7e4349f2c042989d80c18a0459bbaa8
+size 605509
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..de957e30f0d5b83931501b114035720d490d0371
--- /dev/null
+++ b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,58 @@
+{
+ "results": {
+ "winogrande": {
+ "acc,none": 0.6827150749802684,
+ "acc_stderr,none": 0.013080598411332125,
+ "alias": "winogrande"
+ }
+ },
+ "configs": {
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "winogrande": 1.0
+ },
+ "n-shot": {
+ "winogrande": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+version https://git-lfs.github.com/spec/v1
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+size 8983
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..4d8ab65c08d57fcd51217e9485e548498e03f86d
--- /dev/null
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@@ -0,0 +1,390 @@
+{
+ "results": {
+ "xcopa": {
+ "acc,none": 0.6223636363636362,
+ "acc_stderr,none": 0.07095721581010465,
+ "alias": "xcopa"
+ },
+ "xcopa_et": {
+ "acc,none": 0.584,
+ "acc_stderr,none": 0.022064943313928862,
+ "alias": " - xcopa_et"
+ },
+ "xcopa_ht": {
+ "acc,none": 0.53,
+ "acc_stderr,none": 0.022342748192502846,
+ "alias": " - xcopa_ht"
+ },
+ "xcopa_id": {
+ "acc,none": 0.722,
+ "acc_stderr,none": 0.020055833888070924,
+ "alias": " - xcopa_id"
+ },
+ "xcopa_it": {
+ "acc,none": 0.74,
+ "acc_stderr,none": 0.019635965529725512,
+ "alias": " - xcopa_it"
+ },
+ "xcopa_qu": {
+ "acc,none": 0.506,
+ "acc_stderr,none": 0.022381462412439324,
+ "alias": " - xcopa_qu"
+ },
+ "xcopa_sw": {
+ "acc,none": 0.55,
+ "acc_stderr,none": 0.02227087748536044,
+ "alias": " - xcopa_sw"
+ },
+ "xcopa_ta": {
+ "acc,none": 0.582,
+ "acc_stderr,none": 0.022080014812228137,
+ "alias": " - xcopa_ta"
+ },
+ "xcopa_th": {
+ "acc,none": 0.582,
+ "acc_stderr,none": 0.022080014812228137,
+ "alias": " - xcopa_th"
+ },
+ "xcopa_tr": {
+ "acc,none": 0.638,
+ "acc_stderr,none": 0.021513662527582408,
+ "alias": " - xcopa_tr"
+ },
+ "xcopa_vi": {
+ "acc,none": 0.708,
+ "acc_stderr,none": 0.02035437548053008,
+ "alias": " - xcopa_vi"
+ },
+ "xcopa_zh": {
+ "acc,none": 0.704,
+ "acc_stderr,none": 0.020435342091896135,
+ "alias": " - xcopa_zh"
+ }
+ },
+ "groups": {
+ "xcopa": {
+ "acc,none": 0.6223636363636362,
+ "acc_stderr,none": 0.07095721581010465,
+ "alias": "xcopa"
+ }
+ },
+ "configs": {
+ "xcopa_et": {
+ "task": "xcopa_et",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "et",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'sest', 'effect': 'seetõttu'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ht": {
+ "task": "xcopa_ht",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ht",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'poukisa', 'effect': 'donk sa'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_id": {
+ "task": "xcopa_id",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "id",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'karena', 'effect': 'maka'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_it": {
+ "task": "xcopa_it",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "it",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'perché', 'effect': 'quindi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_qu": {
+ "task": "xcopa_qu",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "qu",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'imataq', 'effect': 'chaymi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_sw": {
+ "task": "xcopa_sw",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "sw",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ta": {
+ "task": "xcopa_ta",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ta",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_th": {
+ "task": "xcopa_th",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "th",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_tr": {
+ "task": "xcopa_tr",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "tr",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_vi": {
+ "task": "xcopa_vi",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "vi",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_zh": {
+ "task": "xcopa_zh",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "zh",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': '因为', 'effect': '所以'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "xcopa": "N/A",
+ "xcopa_et": 1.0,
+ "xcopa_ht": 1.0,
+ "xcopa_id": 1.0,
+ "xcopa_it": 1.0,
+ "xcopa_qu": 1.0,
+ "xcopa_sw": 1.0,
+ "xcopa_ta": 1.0,
+ "xcopa_th": 1.0,
+ "xcopa_tr": 1.0,
+ "xcopa_vi": 1.0,
+ "xcopa_zh": 1.0
+ },
+ "n-shot": {
+ "xcopa": 0,
+ "xcopa_et": 0,
+ "xcopa_ht": 0,
+ "xcopa_id": 0,
+ "xcopa_it": 0,
+ "xcopa_qu": 0,
+ "xcopa_sw": 0,
+ "xcopa_ta": 0,
+ "xcopa_th": 0,
+ "xcopa_tr": 0,
+ "xcopa_vi": 0,
+ "xcopa_zh": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": " - xnli_de"
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+ "alias": " - xnli_el"
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+ "alias": " - xnli_en"
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+ "alias": " - xnli_es"
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+ "alias": " - xnli_fr"
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+ "alias": " - xnli_hi"
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+ "alias": " - xnli_ru"
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+ "acc_stderr,none": 0.009795906230304215,
+ "alias": " - xnli_sw"
+ },
+ "xnli_th": {
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+ "acc_stderr,none": 0.0098449990344642,
+ "alias": " - xnli_th"
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+ "acc_stderr,none": 0.009964722457358776,
+ "alias": " - xnli_tr"
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+ "alias": " - xnli_ur"
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+ "acc_stderr,none": 0.009923711675408058,
+ "alias": " - xnli_vi"
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+ "acc_stderr,none": 0.00950965914301563,
+ "alias": " - xnli_zh"
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+ "doc_to_text": "",
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+ "description": "",
+ "target_delimiter": " ",
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+ "training_split": "train",
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+ "xwinograd"
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+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
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+ "xwinograd"
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+ "dataset_path": "Muennighoff/xwinograd",
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+ "xwinograd"
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8-no-cuda-with-warmup/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8/nq_open/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-1-8/nq_open/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "anli"
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+ "config": {
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+ "batch_size": "auto",
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+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
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+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/blimp/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": " - blimp_drop_argument"
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+ "alias": " - blimp_ellipsis_n_bar_1"
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+ "alias": " - blimp_existential_there_quantifiers_1"
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+ "acc_stderr,none": 0.014853842487270333,
+ "alias": " - blimp_existential_there_quantifiers_2"
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+ "acc_stderr,none": 0.009363689373248118,
+ "alias": " - blimp_existential_there_subject_raising"
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+ "alias": " - blimp_inchoative"
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+ "alias": " - blimp_wh_questions_object_gap"
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+ "alias": " - blimp_wh_questions_subject_gap_long_distance"
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+ "description": "以下是关于农学的单项选择题,请直接给出正确答案的选项。\n\n",
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+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "description": "以下是关于解剖学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "description": "以下是关于古汉语的单项选择题,请直接给出正确答案的选项。\n\n",
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+ "description": "以下是关于艺术学的单项选择题,请直接给出正确答案的选项。\n\n",
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+ "description": "以下是关于天文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于商业伦理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_civil_service_exam": {
+ "task": "cmmlu_chinese_civil_service_exam",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_civil_service_exam",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国公务员考试的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_driving_rule": {
+ "task": "cmmlu_chinese_driving_rule",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_driving_rule",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国驾驶规则的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_food_culture": {
+ "task": "cmmlu_chinese_food_culture",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_food_culture",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国饮食文化的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_foreign_policy": {
+ "task": "cmmlu_chinese_foreign_policy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国外交政策的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_history": {
+ "task": "cmmlu_chinese_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_literature": {
+ "task": "cmmlu_chinese_literature",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_literature",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_teacher_qualification": {
+ "task": "cmmlu_chinese_teacher_qualification",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_teacher_qualification",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国教师资格的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_clinical_knowledge": {
+ "task": "cmmlu_clinical_knowledge",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于临床知识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_actuarial_science": {
+ "task": "cmmlu_college_actuarial_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_actuarial_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学精算学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_education": {
+ "task": "cmmlu_college_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_engineering_hydrology": {
+ "task": "cmmlu_college_engineering_hydrology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_engineering_hydrology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学工程水文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_law": {
+ "task": "cmmlu_college_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学法律的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_mathematics": {
+ "task": "cmmlu_college_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medical_statistics": {
+ "task": "cmmlu_college_medical_statistics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medical_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学统计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medicine": {
+ "task": "cmmlu_college_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_science": {
+ "task": "cmmlu_computer_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_security": {
+ "task": "cmmlu_computer_security",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机安全的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_conceptual_physics": {
+ "task": "cmmlu_conceptual_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于概念物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_construction_project_management": {
+ "task": "cmmlu_construction_project_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "construction_project_management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于建设工程管理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_economics": {
+ "task": "cmmlu_economics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "economics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于经济学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_education": {
+ "task": "cmmlu_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_electrical_engineering": {
+ "task": "cmmlu_electrical_engineering",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于电气工程的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_chinese": {
+ "task": "cmmlu_elementary_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学语文的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_commonsense": {
+ "task": "cmmlu_elementary_commonsense",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_commonsense",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学常识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_information_and_technology": {
+ "task": "cmmlu_elementary_information_and_technology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_information_and_technology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学信息技术的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_mathematics": {
+ "task": "cmmlu_elementary_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于初等数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_ethnology": {
+ "task": "cmmlu_ethnology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "ethnology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于民族学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_food_science": {
+ "task": "cmmlu_food_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "food_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于食品科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_genetics": {
+ "task": "cmmlu_genetics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于遗传学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_global_facts": {
+ "task": "cmmlu_global_facts",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于全球事实的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_biology": {
+ "task": "cmmlu_high_school_biology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中生物的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_chemistry": {
+ "task": "cmmlu_high_school_chemistry",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中化学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_geography": {
+ "task": "cmmlu_high_school_geography",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中地理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_mathematics": {
+ "task": "cmmlu_high_school_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_physics": {
+ "task": "cmmlu_high_school_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_politics": {
+ "task": "cmmlu_high_school_politics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中政治的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_human_sexuality": {
+ "task": "cmmlu_human_sexuality",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于人类性行为的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_international_law": {
+ "task": "cmmlu_international_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于国际法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_journalism": {
+ "task": "cmmlu_journalism",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "journalism",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于新闻学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_jurisprudence": {
+ "task": "cmmlu_jurisprudence",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_legal_and_moral_basis": {
+ "task": "cmmlu_legal_and_moral_basis",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "legal_and_moral_basis",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法律与道德基础的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_logical": {
+ "task": "cmmlu_logical",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "logical",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于逻辑学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_machine_learning": {
+ "task": "cmmlu_machine_learning",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于机器学习的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_management": {
+ "task": "cmmlu_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于管理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marketing": {
+ "task": "cmmlu_marketing",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于市场营销的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marxist_theory": {
+ "task": "cmmlu_marxist_theory",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marxist_theory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于马克思主义理论的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_modern_chinese": {
+ "task": "cmmlu_modern_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "modern_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于现代汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_nutrition": {
+ "task": "cmmlu_nutrition",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于营养学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_philosophy": {
+ "task": "cmmlu_philosophy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于哲学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_accounting": {
+ "task": "cmmlu_professional_accounting",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业会计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_law": {
+ "task": "cmmlu_professional_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_medicine": {
+ "task": "cmmlu_professional_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_psychology": {
+ "task": "cmmlu_professional_psychology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业心理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_public_relations": {
+ "task": "cmmlu_public_relations",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于公共关系的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
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+ "higher_is_better": true
+ }
+ ],
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+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_security_study": {
+ "task": "cmmlu_security_study",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "security_study",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于安全研究的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sociology": {
+ "task": "cmmlu_sociology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于社会学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sports_science": {
+ "task": "cmmlu_sports_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sports_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于体育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ {
+ "metric": "acc_norm",
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_traditional_chinese_medicine": {
+ "task": "cmmlu_traditional_chinese_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "traditional_chinese_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中医中药的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "metadata": {
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+ },
+ "cmmlu_virology": {
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+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于病毒学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "cmmlu_world_history": {
+ "task": "cmmlu_world_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
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+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_world_religions": {
+ "task": "cmmlu_world_religions",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界宗教的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ }
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+ }
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/copa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/copa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "copa"
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+ "doc_to_target": "def doc_to_target(doc):\n correct_choice = doc[\"choice1\"] if doc[\"label\"] == 0 else doc[\"choice2\"]\n # Connect the sentences\n return \" \" + convert_choice(correct_choice)\n",
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+ "alias": "logiqa"
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+ "acc_stderr,none": 0.034373055019806184
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+ "mmlu_high_school_government_and_politics": {
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+ "mmlu_stem": {
+ "alias": " - stem",
+ "acc,none": 0.2581668252457976,
+ "acc_stderr,none": 0.05829306180032575
+ },
+ "mmlu_abstract_algebra": {
+ "alias": " - abstract_algebra",
+ "acc,none": 0.21,
+ "acc_stderr,none": 0.040936018074033256
+ },
+ "mmlu_anatomy": {
+ "alias": " - anatomy",
+ "acc,none": 0.3333333333333333,
+ "acc_stderr,none": 0.04072314811876837
+ },
+ "mmlu_astronomy": {
+ "alias": " - astronomy",
+ "acc,none": 0.27631578947368424,
+ "acc_stderr,none": 0.03639057569952925
+ },
+ "mmlu_college_biology": {
+ "alias": " - college_biology",
+ "acc,none": 0.3055555555555556,
+ "acc_stderr,none": 0.03852084696008534
+ },
+ "mmlu_college_chemistry": {
+ "alias": " - college_chemistry",
+ "acc,none": 0.31,
+ "acc_stderr,none": 0.04648231987117316
+ },
+ "mmlu_college_computer_science": {
+ "alias": " - college_computer_science",
+ "acc,none": 0.24,
+ "acc_stderr,none": 0.042923469599092816
+ },
+ "mmlu_college_mathematics": {
+ "alias": " - college_mathematics",
+ "acc,none": 0.22,
+ "acc_stderr,none": 0.04163331998932269
+ },
+ "mmlu_college_physics": {
+ "alias": " - college_physics",
+ "acc,none": 0.17647058823529413,
+ "acc_stderr,none": 0.0379328118530781
+ },
+ "mmlu_computer_security": {
+ "alias": " - computer_security",
+ "acc,none": 0.35,
+ "acc_stderr,none": 0.0479372485441102
+ },
+ "mmlu_conceptual_physics": {
+ "alias": " - conceptual_physics",
+ "acc,none": 0.2978723404255319,
+ "acc_stderr,none": 0.029896145682095455
+ },
+ "mmlu_electrical_engineering": {
+ "alias": " - electrical_engineering",
+ "acc,none": 0.2896551724137931,
+ "acc_stderr,none": 0.03780019230438014
+ },
+ "mmlu_elementary_mathematics": {
+ "alias": " - elementary_mathematics",
+ "acc,none": 0.20634920634920634,
+ "acc_stderr,none": 0.02084229093011466
+ },
+ "mmlu_high_school_biology": {
+ "alias": " - high_school_biology",
+ "acc,none": 0.35161290322580646,
+ "acc_stderr,none": 0.027162537826948458
+ },
+ "mmlu_high_school_chemistry": {
+ "alias": " - high_school_chemistry",
+ "acc,none": 0.2019704433497537,
+ "acc_stderr,none": 0.02824735012218027
+ },
+ "mmlu_high_school_computer_science": {
+ "alias": " - high_school_computer_science",
+ "acc,none": 0.27,
+ "acc_stderr,none": 0.044619604333847394
+ },
+ "mmlu_high_school_mathematics": {
+ "alias": " - high_school_mathematics",
+ "acc,none": 0.21851851851851853,
+ "acc_stderr,none": 0.025195752251823793
+ },
+ "mmlu_high_school_physics": {
+ "alias": " - high_school_physics",
+ "acc,none": 0.2251655629139073,
+ "acc_stderr,none": 0.03410435282008936
+ },
+ "mmlu_high_school_statistics": {
+ "alias": " - high_school_statistics",
+ "acc,none": 0.16666666666666666,
+ "acc_stderr,none": 0.025416428388767478
+ },
+ "mmlu_machine_learning": {
+ "alias": " - machine_learning",
+ "acc,none": 0.32142857142857145,
+ "acc_stderr,none": 0.044328040552915185
+ }
+ },
+ "groups": {
+ "mmlu": {
+ "acc,none": 0.3046574562028201,
+ "acc_stderr,none": 0.05903992247693278,
+ "alias": "mmlu"
+ },
+ "mmlu_humanities": {
+ "alias": " - humanities",
+ "acc,none": 0.29436769394261425,
+ "acc_stderr,none": 0.0528372493870733
+ },
+ "mmlu_other": {
+ "alias": " - other",
+ "acc,none": 0.3601544898616029,
+ "acc_stderr,none": 0.04733464951680367
+ },
+ "mmlu_social_sciences": {
+ "alias": " - social_sciences",
+ "acc,none": 0.31199220019499513,
+ "acc_stderr,none": 0.053246591909246396
+ },
+ "mmlu_stem": {
+ "alias": " - stem",
+ "acc,none": 0.2581668252457976,
+ "acc_stderr,none": 0.05829306180032575
+ }
+ },
+ "configs": {
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
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+ "repeats": 1,
+ "should_decontaminate": false,
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+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
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+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
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+ "alias": "nq_open"
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+ "task": "nq_open",
+ "dataset_path": "nq_open",
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+ "version": 3.0
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+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_transitive": {
+ "task": "blimp_transitive",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "transitive",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_island": {
+ "task": "blimp_wh_island",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_island",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_questions_object_gap": {
+ "task": "blimp_wh_questions_object_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_questions_object_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_questions_subject_gap": {
+ "task": "blimp_wh_questions_subject_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_questions_subject_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_questions_subject_gap_long_distance": {
+ "task": "blimp_wh_questions_subject_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_questions_subject_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap": {
+ "task": "blimp_wh_vs_that_no_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap_long_distance": {
+ "task": "blimp_wh_vs_that_no_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap": {
+ "task": "blimp_wh_vs_that_with_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap_long_distance": {
+ "task": "blimp_wh_vs_that_with_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "lambada_openai": {
+ "task": "lambada_openai",
+ "group": [
+ "lambada"
+ ],
+ "dataset_path": "EleutherAI/lambada_openai",
+ "dataset_name": "default",
+ "test_split": "test",
+ "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+ "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "perplexity",
+ "aggregation": "perplexity",
+ "higher_is_better": false
+ },
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "loglikelihood",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{text}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "logiqa": {
+ "task": "logiqa",
+ "dataset_path": "EleutherAI/logiqa",
+ "dataset_name": "logiqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: \n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
+ "doc_to_target": "def doc_to_target(doc) -> int:\n choices = [\"a\", \"b\", \"c\", \"d\"]\n return choices.index(doc[\"label\"].strip())\n",
+ "doc_to_choice": "{{options}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{context}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "piqa": {
+ "task": "piqa",
+ "dataset_path": "piqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Question: {{goal}}\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[sol1, sol2]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "goal",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "sciq": {
+ "task": "sciq",
+ "dataset_path": "sciq",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
+ "doc_to_target": 3,
+ "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{support}} {{question}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "word_perplexity"
+ },
+ {
+ "metric": "byte_perplexity"
+ },
+ {
+ "metric": "bits_per_byte"
+ }
+ ],
+ "output_type": "loglikelihood_rolling",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wsc": {
+ "task": "wsc",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wsc.fixed",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "ai2_arc": "N/A",
+ "arc_challenge": 1.0,
+ "arc_easy": 1.0,
+ "blimp": "N/A",
+ "blimp_adjunct_island": 1.0,
+ "blimp_anaphor_gender_agreement": 1.0,
+ "blimp_anaphor_number_agreement": 1.0,
+ "blimp_animate_subject_passive": 1.0,
+ "blimp_animate_subject_trans": 1.0,
+ "blimp_causative": 1.0,
+ "blimp_complex_NP_island": 1.0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 1.0,
+ "blimp_coordinate_structure_constraint_object_extraction": 1.0,
+ "blimp_determiner_noun_agreement_1": 1.0,
+ "blimp_determiner_noun_agreement_2": 1.0,
+ "blimp_determiner_noun_agreement_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 1.0,
+ "blimp_distractor_agreement_relational_noun": 1.0,
+ "blimp_distractor_agreement_relative_clause": 1.0,
+ "blimp_drop_argument": 1.0,
+ "blimp_ellipsis_n_bar_1": 1.0,
+ "blimp_ellipsis_n_bar_2": 1.0,
+ "blimp_existential_there_object_raising": 1.0,
+ "blimp_existential_there_quantifiers_1": 1.0,
+ "blimp_existential_there_quantifiers_2": 1.0,
+ "blimp_existential_there_subject_raising": 1.0,
+ "blimp_expletive_it_object_raising": 1.0,
+ "blimp_inchoative": 1.0,
+ "blimp_intransitive": 1.0,
+ "blimp_irregular_past_participle_adjectives": 1.0,
+ "blimp_irregular_past_participle_verbs": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_left_branch_island_echo_question": 1.0,
+ "blimp_left_branch_island_simple_question": 1.0,
+ "blimp_matrix_question_npi_licensor_present": 1.0,
+ "blimp_npi_present_1": 1.0,
+ "blimp_npi_present_2": 1.0,
+ "blimp_only_npi_licensor_present": 1.0,
+ "blimp_only_npi_scope": 1.0,
+ "blimp_passive_1": 1.0,
+ "blimp_passive_2": 1.0,
+ "blimp_principle_A_c_command": 1.0,
+ "blimp_principle_A_case_1": 1.0,
+ "blimp_principle_A_case_2": 1.0,
+ "blimp_principle_A_domain_1": 1.0,
+ "blimp_principle_A_domain_2": 1.0,
+ "blimp_principle_A_domain_3": 1.0,
+ "blimp_principle_A_reconstruction": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_sentential_negation_npi_licensor_present": 1.0,
+ "blimp_sentential_negation_npi_scope": 1.0,
+ "blimp_sentential_subject_island": 1.0,
+ "blimp_superlative_quantifiers_1": 1.0,
+ "blimp_superlative_quantifiers_2": 1.0,
+ "blimp_tough_vs_raising_1": 1.0,
+ "blimp_tough_vs_raising_2": 1.0,
+ "blimp_transitive": 1.0,
+ "blimp_wh_island": 1.0,
+ "blimp_wh_questions_object_gap": 1.0,
+ "blimp_wh_questions_subject_gap": 1.0,
+ "blimp_wh_questions_subject_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_no_gap": 1.0,
+ "blimp_wh_vs_that_no_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_with_gap": 1.0,
+ "blimp_wh_vs_that_with_gap_long_distance": 1.0,
+ "lambada_openai": 1.0,
+ "logiqa": 1.0,
+ "mmlu": "N/A",
+ "mmlu_abstract_algebra": 0.0,
+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
+ "mmlu_college_computer_science": 0.0,
+ "mmlu_college_mathematics": 0.0,
+ "mmlu_college_medicine": 0.0,
+ "mmlu_college_physics": 0.0,
+ "mmlu_computer_security": 0.0,
+ "mmlu_conceptual_physics": 0.0,
+ "mmlu_econometrics": 0.0,
+ "mmlu_electrical_engineering": 0.0,
+ "mmlu_elementary_mathematics": 0.0,
+ "mmlu_formal_logic": 0.0,
+ "mmlu_global_facts": 0.0,
+ "mmlu_high_school_biology": 0.0,
+ "mmlu_high_school_chemistry": 0.0,
+ "mmlu_high_school_computer_science": 0.0,
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+ "rouge1_diff_stderr,none": 0.9524042925993831,
+ "rouge2_max,none": 36.58364933117119,
+ "rouge2_max_stderr,none": 1.0455110530341567,
+ "rouge2_acc,none": 0.25703794369645044,
+ "rouge2_acc_stderr,none": 0.015298077509485083,
+ "rouge2_diff,none": -11.717572069837749,
+ "rouge2_diff_stderr,none": 1.1578435886750256,
+ "rougeL_max,none": 49.93512143971857,
+ "rougeL_max_stderr,none": 0.9035769686215327,
+ "rougeL_acc,none": 0.2827417380660955,
+ "rougeL_acc_stderr,none": 0.015764770836777308,
+ "rougeL_diff,none": -10.00717961692408,
+ "rougeL_diff_stderr,none": 0.9684057908961523,
+ "alias": "truthfulqa"
+ }
+ },
+ "configs": {
+ "truthfulqa_gen": {
+ "task": "truthfulqa_gen",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "generation",
+ "validation_split": "validation",
+ "process_docs": "def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset:\n return dataset.map(preprocess_function)\n",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
+ "doc_to_target": " ",
+ "process_results": "def process_results_gen(doc, results):\n completion = results[0]\n true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n all_refs = true_refs + false_refs\n\n # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n # # BLEURT\n # bleurt_scores_true = self.bleurt.compute(\n # predictions=[completion] * len(true_refs), references=true_refs\n # )[\"scores\"]\n # bleurt_scores_false = self.bleurt.compute(\n # predictions=[completion] * len(false_refs), references=false_refs\n # )[\"scores\"]\n # bleurt_correct = max(bleurt_scores_true)\n # bleurt_incorrect = max(bleurt_scores_false)\n # bleurt_max = bleurt_correct\n # bleurt_diff = bleurt_correct - bleurt_incorrect\n # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n # BLEU\n bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n bleu_max = bleu_correct\n bleu_diff = bleu_correct - bleu_incorrect\n bleu_acc = int(bleu_correct > bleu_incorrect)\n\n # ROUGE-N\n rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n # ROUGE-1\n rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n rouge1_max = rouge1_correct\n rouge1_diff = rouge1_correct - rouge1_incorrect\n rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n # ROUGE-2\n rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n rouge2_max = rouge2_correct\n rouge2_diff = rouge2_correct - rouge2_incorrect\n rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n # ROUGE-L\n rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n rougeL_max = rougeL_correct\n rougeL_diff = rougeL_correct - rougeL_incorrect\n rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n return {\n # \"bleurt_max\": bleurt_max,\n # \"bleurt_acc\": bleurt_acc,\n # \"bleurt_diff\": bleurt_diff,\n \"bleu_max\": bleu_max,\n \"bleu_acc\": bleu_acc,\n \"bleu_diff\": bleu_diff,\n \"rouge1_max\": rouge1_max,\n \"rouge1_acc\": rouge1_acc,\n \"rouge1_diff\": rouge1_diff,\n \"rouge2_max\": rouge2_max,\n \"rouge2_acc\": rouge2_acc,\n \"rouge2_diff\": rouge2_diff,\n \"rougeL_max\": rougeL_max,\n \"rougeL_acc\": rougeL_acc,\n \"rougeL_diff\": rougeL_diff,\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "bleu_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "generate_until",
+ "generation_kwargs": {
+ "until": [
+ "\n\n"
+ ],
+ "do_sample": false
+ },
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 3.0
+ }
+ },
+ "truthfulqa_mc1": {
+ "task": "truthfulqa_mc1",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc1_targets.choices}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "truthfulqa_mc2": {
+ "task": "truthfulqa_mc2",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc2_targets.choices}}",
+ "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "truthfulqa": "N/A",
+ "truthfulqa_gen": 3.0,
+ "truthfulqa_mc1": 2.0,
+ "truthfulqa_mc2": 2.0
+ },
+ "n-shot": {
+ "truthfulqa": 0,
+ "truthfulqa_gen": 0,
+ "truthfulqa_mc1": 0,
+ "truthfulqa_mc2": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk-blink_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
index 0000000000000000000000000000000000000000..d2ff9016b945ede4aa1100ab7565418b8b7a11e3
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+++ b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+version https://git-lfs.github.com/spec/v1
+oid sha256:fbb7a8ae2d66d07d64210a477fa7e1ec1db3bab640da5da0caf79c13d5499e7b
+size 550030
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..159cdae71d7f53c51b5797fe3d509311fce99c5f
--- /dev/null
+++ b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,58 @@
+{
+ "results": {
+ "winogrande": {
+ "acc,none": 0.6740331491712708,
+ "acc_stderr,none": 0.013173782636922187,
+ "alias": "winogrande"
+ }
+ },
+ "configs": {
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "winogrande": 1.0
+ },
+ "n-shot": {
+ "winogrande": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk-blink_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
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+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
index 0000000000000000000000000000000000000000..0aa000fb21d1edd154b50c3d8a7229432dd9ee89
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+size 39944
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..c5af63c011d78a82a5974904531e7050f48f79df
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+{
+ "results": {
+ "xcopa": {
+ "acc,none": 0.6205454545454545,
+ "acc_stderr,none": 0.06678889272508182,
+ "alias": "xcopa"
+ },
+ "xcopa_et": {
+ "acc,none": 0.586,
+ "acc_stderr,none": 0.022049497969827865,
+ "alias": " - xcopa_et"
+ },
+ "xcopa_ht": {
+ "acc,none": 0.528,
+ "acc_stderr,none": 0.022347949832668086,
+ "alias": " - xcopa_ht"
+ },
+ "xcopa_id": {
+ "acc,none": 0.72,
+ "acc_stderr,none": 0.02009995064750323,
+ "alias": " - xcopa_id"
+ },
+ "xcopa_it": {
+ "acc,none": 0.738,
+ "acc_stderr,none": 0.019684688820194723,
+ "alias": " - xcopa_it"
+ },
+ "xcopa_qu": {
+ "acc,none": 0.51,
+ "acc_stderr,none": 0.02237859698923078,
+ "alias": " - xcopa_qu"
+ },
+ "xcopa_sw": {
+ "acc,none": 0.548,
+ "acc_stderr,none": 0.022279694107843428,
+ "alias": " - xcopa_sw"
+ },
+ "xcopa_ta": {
+ "acc,none": 0.58,
+ "acc_stderr,none": 0.02209471322976178,
+ "alias": " - xcopa_ta"
+ },
+ "xcopa_th": {
+ "acc,none": 0.578,
+ "acc_stderr,none": 0.022109039310618552,
+ "alias": " - xcopa_th"
+ },
+ "xcopa_tr": {
+ "acc,none": 0.64,
+ "acc_stderr,none": 0.021487751089720522,
+ "alias": " - xcopa_tr"
+ },
+ "xcopa_vi": {
+ "acc,none": 0.71,
+ "acc_stderr,none": 0.020313179231745197,
+ "alias": " - xcopa_vi"
+ },
+ "xcopa_zh": {
+ "acc,none": 0.688,
+ "acc_stderr,none": 0.02074059653648807,
+ "alias": " - xcopa_zh"
+ }
+ },
+ "groups": {
+ "xcopa": {
+ "acc,none": 0.6205454545454545,
+ "acc_stderr,none": 0.06678889272508182,
+ "alias": "xcopa"
+ }
+ },
+ "configs": {
+ "xcopa_et": {
+ "task": "xcopa_et",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "et",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'sest', 'effect': 'seetõttu'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ht": {
+ "task": "xcopa_ht",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ht",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'poukisa', 'effect': 'donk sa'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_id": {
+ "task": "xcopa_id",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "id",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'karena', 'effect': 'maka'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_it": {
+ "task": "xcopa_it",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "it",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'perché', 'effect': 'quindi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_qu": {
+ "task": "xcopa_qu",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "qu",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'imataq', 'effect': 'chaymi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_sw": {
+ "task": "xcopa_sw",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "sw",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ta": {
+ "task": "xcopa_ta",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ta",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_th": {
+ "task": "xcopa_th",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "th",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_tr": {
+ "task": "xcopa_tr",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "tr",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_vi": {
+ "task": "xcopa_vi",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "vi",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_zh": {
+ "task": "xcopa_zh",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "zh",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': '因为', 'effect': '所以'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "xcopa": "N/A",
+ "xcopa_et": 1.0,
+ "xcopa_ht": 1.0,
+ "xcopa_id": 1.0,
+ "xcopa_it": 1.0,
+ "xcopa_qu": 1.0,
+ "xcopa_sw": 1.0,
+ "xcopa_ta": 1.0,
+ "xcopa_th": 1.0,
+ "xcopa_tr": 1.0,
+ "xcopa_vi": 1.0,
+ "xcopa_zh": 1.0
+ },
+ "n-shot": {
+ "xcopa": 0,
+ "xcopa_et": 0,
+ "xcopa_ht": 0,
+ "xcopa_id": 0,
+ "xcopa_it": 0,
+ "xcopa_qu": 0,
+ "xcopa_sw": 0,
+ "xcopa_ta": 0,
+ "xcopa_th": 0,
+ "xcopa_tr": 0,
+ "xcopa_vi": 0,
+ "xcopa_zh": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk-blink_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
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+size 70691
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..2ab4ea5ed9f929daa133b23028aa51df7786d4e9
--- /dev/null
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+ "alias": "xnli"
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+ "alias": " - xnli_ar"
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+ "acc,none": 0.4895582329317269,
+ "acc_stderr,none": 0.01001988720567743,
+ "alias": " - xnli_de"
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+ "xnli_el": {
+ "acc,none": 0.39477911646586344,
+ "acc_stderr,none": 0.00979764252169086,
+ "alias": " - xnli_el"
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+ "acc_stderr,none": 0.010010812905412057,
+ "alias": " - xnli_en"
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+ "xnli_es": {
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+ "acc_stderr,none": 0.010018551648218462,
+ "alias": " - xnli_es"
+ },
+ "xnli_fr": {
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+ "acc_stderr,none": 0.010020647068114175,
+ "alias": " - xnli_fr"
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+ "acc_stderr,none": 0.00992820318611292,
+ "alias": " - xnli_hi"
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+ "acc,none": 0.4867469879518072,
+ "acc_stderr,none": 0.010018551648218459,
+ "alias": " - xnli_ru"
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+ "acc,none": 0.385140562248996,
+ "acc_stderr,none": 0.00975405283095075,
+ "alias": " - xnli_sw"
+ },
+ "xnli_th": {
+ "acc,none": 0.40803212851405624,
+ "acc_stderr,none": 0.009851078965044868,
+ "alias": " - xnli_th"
+ },
+ "xnli_tr": {
+ "acc,none": 0.4433734939759036,
+ "acc_stderr,none": 0.009957592660538646,
+ "alias": " - xnli_tr"
+ },
+ "xnli_ur": {
+ "acc,none": 0.40562248995983935,
+ "acc_stderr,none": 0.00984191815616317,
+ "alias": " - xnli_ur"
+ },
+ "xnli_vi": {
+ "acc,none": 0.42329317269076305,
+ "acc_stderr,none": 0.009903432138272914,
+ "alias": " - xnli_vi"
+ },
+ "xnli_zh": {
+ "acc,none": 0.3461847389558233,
+ "acc_stderr,none": 0.009536061379898332,
+ "alias": " - xnli_zh"
+ }
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+ "groups": {
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+ "acc_stderr,none": 0.04719083714111022,
+ "alias": "xnli"
+ }
+ },
+ "configs": {
+ "xnli_ar": {
+ "task": "xnli_ar",
+ "group": "xnli",
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+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", صحيح? نعم, \"+hypothesis,premise+\", صحيح? لذا, \"+hypothesis,premise+\", صحيح? رقم, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
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+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xnli_bg": {
+ "task": "xnli_bg",
+ "group": "xnli",
+ "dataset_path": "xnli",
+ "dataset_name": "bg",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", правилно? да, \"+hypothesis,premise+\", правилно? така, \"+hypothesis,premise+\", правилно? не, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "should_decontaminate": false,
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+ "group": "xnli",
+ "dataset_path": "xnli",
+ "dataset_name": "de",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", richtig? Ja, \"+hypothesis,premise+\", richtig? Auch, \"+hypothesis,premise+\", richtig? Nein, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ "xnli_el": {
+ "task": "xnli_el",
+ "group": "xnli",
+ "dataset_path": "xnli",
+ "dataset_name": "el",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", σωστός? Ναί, \"+hypothesis,premise+\", σωστός? Έτσι, \"+hypothesis,premise+\", σωστός? όχι, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
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+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xnli_en": {
+ "task": "xnli_en",
+ "group": "xnli",
+ "dataset_path": "xnli",
+ "dataset_name": "en",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", right? Yes, \"+hypothesis,premise+\", right? Also, \"+hypothesis,premise+\", right? No, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
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+ "should_decontaminate": false,
+ "metadata": {
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+ "xnli_es": {
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+ "group": "xnli",
+ "dataset_path": "xnli",
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+ "doc_to_text": "",
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+ "description": "",
+ "target_delimiter": " ",
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ },
+ "xnli_fr": {
+ "task": "xnli_fr",
+ "group": "xnli",
+ "dataset_path": "xnli",
+ "dataset_name": "fr",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", correct? Oui, \"+hypothesis,premise+\", correct? Aussi, \"+hypothesis,premise+\", correct? Non, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
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+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", सही? हाँ, \"+hypothesis,premise+\", सही? इसलिए, \"+hypothesis,premise+\", सही? नहीं, \"+hypothesis]}}",
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+ "should_decontaminate": false,
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+ "target_delimiter": " ",
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
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+ "doc_to_target": "label",
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+ "xwinograd"
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk-blink/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "doc_to_choice": [
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+ "description": "以下是关于农学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "dataset_name": "anatomy",
+ "test_split": "test",
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+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "description": "以下是关于解剖学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "dataset_name": "ancient_chinese",
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+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "C",
+ "D"
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+ "description": "以下是关于古汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "dataset_name": "arts",
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+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于艺术学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metric_list": [
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+ "dataset_name": "astronomy",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于天文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metric_list": [
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+ "dataset_name": "business_ethics",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
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+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
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+ "description": "以下是关于商业伦理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metric_list": [
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+ "output_type": "multiple_choice",
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+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
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+ "description": "以下是关于中国公务员考试的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "metric_list": [
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+ "D"
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+ "description": "以下是关于中国驾驶规则的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ },
+ "cmmlu_chinese_food_culture": {
+ "task": "cmmlu_chinese_food_culture",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_food_culture",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国饮食文化的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_foreign_policy": {
+ "task": "cmmlu_chinese_foreign_policy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国外交政策的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_history": {
+ "task": "cmmlu_chinese_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_literature": {
+ "task": "cmmlu_chinese_literature",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_literature",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_teacher_qualification": {
+ "task": "cmmlu_chinese_teacher_qualification",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_teacher_qualification",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国教师资格的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_clinical_knowledge": {
+ "task": "cmmlu_clinical_knowledge",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于临床知识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_actuarial_science": {
+ "task": "cmmlu_college_actuarial_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_actuarial_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学精算学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_education": {
+ "task": "cmmlu_college_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_engineering_hydrology": {
+ "task": "cmmlu_college_engineering_hydrology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_engineering_hydrology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学工程水文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_law": {
+ "task": "cmmlu_college_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学法律的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_mathematics": {
+ "task": "cmmlu_college_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medical_statistics": {
+ "task": "cmmlu_college_medical_statistics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medical_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学统计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medicine": {
+ "task": "cmmlu_college_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_science": {
+ "task": "cmmlu_computer_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_security": {
+ "task": "cmmlu_computer_security",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机安全的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_conceptual_physics": {
+ "task": "cmmlu_conceptual_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于概念物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_construction_project_management": {
+ "task": "cmmlu_construction_project_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "construction_project_management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于建设工程管理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_economics": {
+ "task": "cmmlu_economics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "economics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于经济学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_education": {
+ "task": "cmmlu_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_electrical_engineering": {
+ "task": "cmmlu_electrical_engineering",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于电气工程的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_chinese": {
+ "task": "cmmlu_elementary_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学语文的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_commonsense": {
+ "task": "cmmlu_elementary_commonsense",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_commonsense",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学常识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_information_and_technology": {
+ "task": "cmmlu_elementary_information_and_technology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_information_and_technology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学信息技术的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_mathematics": {
+ "task": "cmmlu_elementary_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于初等数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_ethnology": {
+ "task": "cmmlu_ethnology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "ethnology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于民族学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_food_science": {
+ "task": "cmmlu_food_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "food_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于食品科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_genetics": {
+ "task": "cmmlu_genetics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于遗传学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_global_facts": {
+ "task": "cmmlu_global_facts",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于全球事实的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_biology": {
+ "task": "cmmlu_high_school_biology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中生物的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_chemistry": {
+ "task": "cmmlu_high_school_chemistry",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中化学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_geography": {
+ "task": "cmmlu_high_school_geography",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中地理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_mathematics": {
+ "task": "cmmlu_high_school_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_physics": {
+ "task": "cmmlu_high_school_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_politics": {
+ "task": "cmmlu_high_school_politics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中政治的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_human_sexuality": {
+ "task": "cmmlu_human_sexuality",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于人类性行为的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_international_law": {
+ "task": "cmmlu_international_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于国际法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_journalism": {
+ "task": "cmmlu_journalism",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "journalism",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于新闻学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_jurisprudence": {
+ "task": "cmmlu_jurisprudence",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_legal_and_moral_basis": {
+ "task": "cmmlu_legal_and_moral_basis",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "legal_and_moral_basis",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法律与道德基础的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_logical": {
+ "task": "cmmlu_logical",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "logical",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于逻辑学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_machine_learning": {
+ "task": "cmmlu_machine_learning",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于机器学习的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_management": {
+ "task": "cmmlu_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于管理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marketing": {
+ "task": "cmmlu_marketing",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于市场营销的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marxist_theory": {
+ "task": "cmmlu_marxist_theory",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marxist_theory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于马克思主义理论的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_modern_chinese": {
+ "task": "cmmlu_modern_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "modern_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于现代汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_nutrition": {
+ "task": "cmmlu_nutrition",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于营养学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_philosophy": {
+ "task": "cmmlu_philosophy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于哲学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_accounting": {
+ "task": "cmmlu_professional_accounting",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业会计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_law": {
+ "task": "cmmlu_professional_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_medicine": {
+ "task": "cmmlu_professional_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_psychology": {
+ "task": "cmmlu_professional_psychology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业心理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_public_relations": {
+ "task": "cmmlu_public_relations",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于公共关系的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_security_study": {
+ "task": "cmmlu_security_study",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "security_study",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于安全研究的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sociology": {
+ "task": "cmmlu_sociology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于社会学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sports_science": {
+ "task": "cmmlu_sports_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sports_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于体育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_traditional_chinese_medicine": {
+ "task": "cmmlu_traditional_chinese_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "traditional_chinese_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中医中药的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_virology": {
+ "task": "cmmlu_virology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于病毒学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_world_history": {
+ "task": "cmmlu_world_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_world_religions": {
+ "task": "cmmlu_world_religions",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界宗教的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ }
+ },
+ "versions": {
+ "cmmlu": "N/A",
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+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2-blink_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
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+ "limit": null,
+ "bootstrap_iters": 100000,
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+}
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/cmmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/copa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/copa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "results": {
+ "copa": {
+ "acc,none": 0.88,
+ "acc_stderr,none": 0.032659863237109066,
+ "alias": "copa"
+ }
+ },
+ "configs": {
+ "copa": {
+ "task": "copa",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "copa",
+ "training_split": "train",
+ "validation_split": "validation",
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+ "doc_to_target": "def doc_to_target(doc):\n correct_choice = doc[\"choice1\"] if doc[\"label\"] == 0 else doc[\"choice2\"]\n # Connect the sentences\n return \" \" + convert_choice(correct_choice)\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [\" \" + convert_choice(doc[\"choice1\"]), \" \" + convert_choice(doc[\"choice2\"])]\n",
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+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "repeats": 1,
+ "should_decontaminate": false,
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+ "version": 1.0
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+ "versions": {
+ "copa": 1.0
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+ "alias": " - mnli"
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+ "alias": " - wnli"
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+ "mmlu_other": {
+ "alias": " - other",
+ "acc,none": 0.3678789829417444,
+ "acc_stderr,none": 0.04596500725174761
+ },
+ "mmlu_social_sciences": {
+ "alias": " - social_sciences",
+ "acc,none": 0.338641533961651,
+ "acc_stderr,none": 0.05953393064172072
+ },
+ "mmlu_stem": {
+ "alias": " - stem",
+ "acc,none": 0.276244846178243,
+ "acc_stderr,none": 0.06730341822253266
+ }
+ },
+ "configs": {
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
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+ "alias": " - paws_ko"
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+ "alias": " - paws_zh"
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+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap": {
+ "task": "blimp_wh_vs_that_no_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_no_gap_long_distance": {
+ "task": "blimp_wh_vs_that_no_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap": {
+ "task": "blimp_wh_vs_that_with_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap_long_distance": {
+ "task": "blimp_wh_vs_that_with_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "lambada_openai": {
+ "task": "lambada_openai",
+ "group": [
+ "lambada"
+ ],
+ "dataset_path": "EleutherAI/lambada_openai",
+ "dataset_name": "default",
+ "test_split": "test",
+ "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+ "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "perplexity",
+ "aggregation": "perplexity",
+ "higher_is_better": false
+ },
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "loglikelihood",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{text}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "logiqa": {
+ "task": "logiqa",
+ "dataset_path": "EleutherAI/logiqa",
+ "dataset_name": "logiqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: \n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
+ "doc_to_target": "def doc_to_target(doc) -> int:\n choices = [\"a\", \"b\", \"c\", \"d\"]\n return choices.index(doc[\"label\"].strip())\n",
+ "doc_to_choice": "{{options}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{context}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "piqa": {
+ "task": "piqa",
+ "dataset_path": "piqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Question: {{goal}}\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[sol1, sol2]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "goal",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "sciq": {
+ "task": "sciq",
+ "dataset_path": "sciq",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
+ "doc_to_target": 3,
+ "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{support}} {{question}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "word_perplexity"
+ },
+ {
+ "metric": "byte_perplexity"
+ },
+ {
+ "metric": "bits_per_byte"
+ }
+ ],
+ "output_type": "loglikelihood_rolling",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wsc": {
+ "task": "wsc",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wsc.fixed",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "ai2_arc": "N/A",
+ "arc_challenge": 1.0,
+ "arc_easy": 1.0,
+ "blimp": "N/A",
+ "blimp_adjunct_island": 1.0,
+ "blimp_anaphor_gender_agreement": 1.0,
+ "blimp_anaphor_number_agreement": 1.0,
+ "blimp_animate_subject_passive": 1.0,
+ "blimp_animate_subject_trans": 1.0,
+ "blimp_causative": 1.0,
+ "blimp_complex_NP_island": 1.0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 1.0,
+ "blimp_coordinate_structure_constraint_object_extraction": 1.0,
+ "blimp_determiner_noun_agreement_1": 1.0,
+ "blimp_determiner_noun_agreement_2": 1.0,
+ "blimp_determiner_noun_agreement_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 1.0,
+ "blimp_distractor_agreement_relational_noun": 1.0,
+ "blimp_distractor_agreement_relative_clause": 1.0,
+ "blimp_drop_argument": 1.0,
+ "blimp_ellipsis_n_bar_1": 1.0,
+ "blimp_ellipsis_n_bar_2": 1.0,
+ "blimp_existential_there_object_raising": 1.0,
+ "blimp_existential_there_quantifiers_1": 1.0,
+ "blimp_existential_there_quantifiers_2": 1.0,
+ "blimp_existential_there_subject_raising": 1.0,
+ "blimp_expletive_it_object_raising": 1.0,
+ "blimp_inchoative": 1.0,
+ "blimp_intransitive": 1.0,
+ "blimp_irregular_past_participle_adjectives": 1.0,
+ "blimp_irregular_past_participle_verbs": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_left_branch_island_echo_question": 1.0,
+ "blimp_left_branch_island_simple_question": 1.0,
+ "blimp_matrix_question_npi_licensor_present": 1.0,
+ "blimp_npi_present_1": 1.0,
+ "blimp_npi_present_2": 1.0,
+ "blimp_only_npi_licensor_present": 1.0,
+ "blimp_only_npi_scope": 1.0,
+ "blimp_passive_1": 1.0,
+ "blimp_passive_2": 1.0,
+ "blimp_principle_A_c_command": 1.0,
+ "blimp_principle_A_case_1": 1.0,
+ "blimp_principle_A_case_2": 1.0,
+ "blimp_principle_A_domain_1": 1.0,
+ "blimp_principle_A_domain_2": 1.0,
+ "blimp_principle_A_domain_3": 1.0,
+ "blimp_principle_A_reconstruction": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_sentential_negation_npi_licensor_present": 1.0,
+ "blimp_sentential_negation_npi_scope": 1.0,
+ "blimp_sentential_subject_island": 1.0,
+ "blimp_superlative_quantifiers_1": 1.0,
+ "blimp_superlative_quantifiers_2": 1.0,
+ "blimp_tough_vs_raising_1": 1.0,
+ "blimp_tough_vs_raising_2": 1.0,
+ "blimp_transitive": 1.0,
+ "blimp_wh_island": 1.0,
+ "blimp_wh_questions_object_gap": 1.0,
+ "blimp_wh_questions_subject_gap": 1.0,
+ "blimp_wh_questions_subject_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_no_gap": 1.0,
+ "blimp_wh_vs_that_no_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_with_gap": 1.0,
+ "blimp_wh_vs_that_with_gap_long_distance": 1.0,
+ "lambada_openai": 1.0,
+ "logiqa": 1.0,
+ "mmlu": "N/A",
+ "mmlu_abstract_algebra": 0.0,
+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
+ "mmlu_college_computer_science": 0.0,
+ "mmlu_college_mathematics": 0.0,
+ "mmlu_college_medicine": 0.0,
+ "mmlu_college_physics": 0.0,
+ "mmlu_computer_security": 0.0,
+ "mmlu_conceptual_physics": 0.0,
+ "mmlu_econometrics": 0.0,
+ "mmlu_electrical_engineering": 0.0,
+ "mmlu_elementary_mathematics": 0.0,
+ "mmlu_formal_logic": 0.0,
+ "mmlu_global_facts": 0.0,
+ "mmlu_high_school_biology": 0.0,
+ "mmlu_high_school_chemistry": 0.0,
+ "mmlu_high_school_computer_science": 0.0,
+ "mmlu_high_school_european_history": 0.0,
+ "mmlu_high_school_geography": 0.0,
+ "mmlu_high_school_government_and_politics": 0.0,
+ "mmlu_high_school_macroeconomics": 0.0,
+ "mmlu_high_school_mathematics": 0.0,
+ "mmlu_high_school_microeconomics": 0.0,
+ "mmlu_high_school_physics": 0.0,
+ "mmlu_high_school_psychology": 0.0,
+ "mmlu_high_school_statistics": 0.0,
+ "mmlu_high_school_us_history": 0.0,
+ "mmlu_high_school_world_history": 0.0,
+ "mmlu_human_aging": 0.0,
+ "mmlu_human_sexuality": 0.0,
+ "mmlu_humanities": "N/A",
+ "mmlu_international_law": 0.0,
+ "mmlu_jurisprudence": 0.0,
+ "mmlu_logical_fallacies": 0.0,
+ "mmlu_machine_learning": 0.0,
+ "mmlu_management": 0.0,
+ "mmlu_marketing": 0.0,
+ "mmlu_medical_genetics": 0.0,
+ "mmlu_miscellaneous": 0.0,
+ "mmlu_moral_disputes": 0.0,
+ "mmlu_moral_scenarios": 0.0,
+ "mmlu_nutrition": 0.0,
+ "mmlu_other": "N/A",
+ "mmlu_philosophy": 0.0,
+ "mmlu_prehistory": 0.0,
+ "mmlu_professional_accounting": 0.0,
+ "mmlu_professional_law": 0.0,
+ "mmlu_professional_medicine": 0.0,
+ "mmlu_professional_psychology": 0.0,
+ "mmlu_public_relations": 0.0,
+ "mmlu_security_studies": 0.0,
+ "mmlu_social_sciences": "N/A",
+ "mmlu_sociology": 0.0,
+ "mmlu_stem": "N/A",
+ "mmlu_us_foreign_policy": 0.0,
+ "mmlu_virology": 0.0,
+ "mmlu_world_religions": 0.0,
+ "piqa": 1.0,
+ "pythia": "N/A",
+ "sciq": 1.0,
+ "wikitext": 2.0,
+ "winogrande": 1.0,
+ "wsc": 1.0
+ },
+ "n-shot": {
+ "ai2_arc": 0,
+ "arc_challenge": 0,
+ "arc_easy": 0,
+ "blimp": 0,
+ "blimp_adjunct_island": 0,
+ "blimp_anaphor_gender_agreement": 0,
+ "blimp_anaphor_number_agreement": 0,
+ "blimp_animate_subject_passive": 0,
+ "blimp_animate_subject_trans": 0,
+ "blimp_causative": 0,
+ "blimp_complex_NP_island": 0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 0,
+ "blimp_coordinate_structure_constraint_object_extraction": 0,
+ "blimp_determiner_noun_agreement_1": 0,
+ "blimp_determiner_noun_agreement_2": 0,
+ "blimp_determiner_noun_agreement_irregular_1": 0,
+ "blimp_determiner_noun_agreement_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 0,
+ "blimp_distractor_agreement_relational_noun": 0,
+ "blimp_distractor_agreement_relative_clause": 0,
+ "blimp_drop_argument": 0,
+ "blimp_ellipsis_n_bar_1": 0,
+ "blimp_ellipsis_n_bar_2": 0,
+ "blimp_existential_there_object_raising": 0,
+ "blimp_existential_there_quantifiers_1": 0,
+ "blimp_existential_there_quantifiers_2": 0,
+ "blimp_existential_there_subject_raising": 0,
+ "blimp_expletive_it_object_raising": 0,
+ "blimp_inchoative": 0,
+ "blimp_intransitive": 0,
+ "blimp_irregular_past_participle_adjectives": 0,
+ "blimp_irregular_past_participle_verbs": 0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 0,
+ "blimp_left_branch_island_echo_question": 0,
+ "blimp_left_branch_island_simple_question": 0,
+ "blimp_matrix_question_npi_licensor_present": 0,
+ "blimp_npi_present_1": 0,
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+ "blimp_only_npi_licensor_present": 0,
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/pythia/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/pythia/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+ "results": {
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+ "em,none": 0.2633,
+ "em_stderr,none": 0.004404458073939524,
+ "alias": "record"
+ }
+ },
+ "configs": {
+ "record": {
+ "task": "record",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "record",
+ "training_split": "train",
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+ "doc_to_text": "def doc_to_text(doc):\n initial_text, *highlights = doc[\"passage\"].strip().split(\"\\n@highlight\\n\")\n text = initial_text + \"\\n\\n\"\n for highlight in highlights:\n text += f\" - {highlight}.\\n\"\n return text\n",
+ "doc_to_target": "{{answers}}",
+ "doc_to_choice": "{{entities}}",
+ "process_results": "def process_results(doc, results):\n # ReCoRD's evaluation is actually deceptively simple:\n # - Pick the maximum likelihood prediction entity\n # - Evaluate the accuracy and token F1 PER EXAMPLE\n # - Average over all examples\n max_idx = np.argmax(np.array([result[0] for result in results]))\n\n prediction = doc[\"entities\"][max_idx]\n gold_label_set = doc[\"answers\"]\n f1 = metric_max_over_ground_truths(\n squad_metrics.compute_f1, prediction, gold_label_set\n )\n em = metric_max_over_ground_truths(\n squad_metrics.compute_exact, prediction, gold_label_set\n )\n\n return {\n \"f1\": f1,\n \"em\": em,\n }\n",
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+ "aggregation": "mean"
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ "record": 1.0
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+ "acc_norm,none": 0.921,
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+ "alias": "sciq"
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+ "training_split": "train",
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+ "description": "",
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+ ],
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+ "doc_to_decontamination_query": "{{support}} {{question}}",
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+ "version": 1.0
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+ "rougeL_diff,none": -0.12362089855666174,
+ "rougeL_diff_stderr,none": 0.10790551921795612,
+ "alias": " - truthfulqa_gen"
+ },
+ "truthfulqa_mc1": {
+ "acc,none": 0.26438188494492043,
+ "acc_stderr,none": 0.015438211119522502,
+ "alias": " - truthfulqa_mc1"
+ },
+ "truthfulqa_mc2": {
+ "acc,none": 0.41963940024859236,
+ "acc_stderr,none": 0.014214967545774367,
+ "alias": " - truthfulqa_mc2"
+ }
+ },
+ "groups": {
+ "truthfulqa": {
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+ "acc_stderr,none": 0.0017275455606294446,
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+ "rougeL_diff,none": -0.12362089855666174,
+ "rougeL_diff_stderr,none": 0.10790551921795612,
+ "alias": "truthfulqa"
+ }
+ },
+ "configs": {
+ "truthfulqa_gen": {
+ "task": "truthfulqa_gen",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "generation",
+ "validation_split": "validation",
+ "process_docs": "def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset:\n return dataset.map(preprocess_function)\n",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
+ "doc_to_target": " ",
+ "process_results": "def process_results_gen(doc, results):\n completion = results[0]\n true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n all_refs = true_refs + false_refs\n\n # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n # # BLEURT\n # bleurt_scores_true = self.bleurt.compute(\n # predictions=[completion] * len(true_refs), references=true_refs\n # )[\"scores\"]\n # bleurt_scores_false = self.bleurt.compute(\n # predictions=[completion] * len(false_refs), references=false_refs\n # )[\"scores\"]\n # bleurt_correct = max(bleurt_scores_true)\n # bleurt_incorrect = max(bleurt_scores_false)\n # bleurt_max = bleurt_correct\n # bleurt_diff = bleurt_correct - bleurt_incorrect\n # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n # BLEU\n bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n bleu_max = bleu_correct\n bleu_diff = bleu_correct - bleu_incorrect\n bleu_acc = int(bleu_correct > bleu_incorrect)\n\n # ROUGE-N\n rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n # ROUGE-1\n rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n rouge1_max = rouge1_correct\n rouge1_diff = rouge1_correct - rouge1_incorrect\n rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n # ROUGE-2\n rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n rouge2_max = rouge2_correct\n rouge2_diff = rouge2_correct - rouge2_incorrect\n rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n # ROUGE-L\n rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n rougeL_max = rougeL_correct\n rougeL_diff = rougeL_correct - rougeL_incorrect\n rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n return {\n # \"bleurt_max\": bleurt_max,\n # \"bleurt_acc\": bleurt_acc,\n # \"bleurt_diff\": bleurt_diff,\n \"bleu_max\": bleu_max,\n \"bleu_acc\": bleu_acc,\n \"bleu_diff\": bleu_diff,\n \"rouge1_max\": rouge1_max,\n \"rouge1_acc\": rouge1_acc,\n \"rouge1_diff\": rouge1_diff,\n \"rouge2_max\": rouge2_max,\n \"rouge2_acc\": rouge2_acc,\n \"rouge2_diff\": rouge2_diff,\n \"rougeL_max\": rougeL_max,\n \"rougeL_acc\": rougeL_acc,\n \"rougeL_diff\": rougeL_diff,\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "bleu_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "generate_until",
+ "generation_kwargs": {
+ "until": [
+ "\n\n"
+ ],
+ "do_sample": false
+ },
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 3.0
+ }
+ },
+ "truthfulqa_mc1": {
+ "task": "truthfulqa_mc1",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc1_targets.choices}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "truthfulqa_mc2": {
+ "task": "truthfulqa_mc2",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc2_targets.choices}}",
+ "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "truthfulqa": "N/A",
+ "truthfulqa_gen": 3.0,
+ "truthfulqa_mc1": 2.0,
+ "truthfulqa_mc2": 2.0
+ },
+ "n-shot": {
+ "truthfulqa": 0,
+ "truthfulqa_gen": 0,
+ "truthfulqa_mc1": 0,
+ "truthfulqa_mc2": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2-blink_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
index 0000000000000000000000000000000000000000..be1453bed31963b8a8b1733d357a0453994f0d7c
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4c7c2fa7d1041448628b19bf1947007f7472bf9b12ba77cb4d4d556c96e6841f
+size 561127
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..5b763bc59d1c272e9e201d4a7f9d792b7e691690
--- /dev/null
+++ b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,58 @@
+{
+ "results": {
+ "winogrande": {
+ "acc,none": 0.6779794790844514,
+ "acc_stderr,none": 0.013132070202071076,
+ "alias": "winogrande"
+ }
+ },
+ "configs": {
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "winogrande": 1.0
+ },
+ "n-shot": {
+ "winogrande": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2-blink_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
index 0000000000000000000000000000000000000000..4dea38ef1306cb2a16c2be8f3f79ad72e779c0b9
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+version https://git-lfs.github.com/spec/v1
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+size 10415
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..52b34ec6054bee7ce48fe48733ec014007d010a9
--- /dev/null
+++ b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,390 @@
+{
+ "results": {
+ "xcopa": {
+ "acc,none": 0.6247272727272727,
+ "acc_stderr,none": 0.07076815037132106,
+ "alias": "xcopa"
+ },
+ "xcopa_et": {
+ "acc,none": 0.598,
+ "acc_stderr,none": 0.021948929609938612,
+ "alias": " - xcopa_et"
+ },
+ "xcopa_ht": {
+ "acc,none": 0.526,
+ "acc_stderr,none": 0.022352791650914163,
+ "alias": " - xcopa_ht"
+ },
+ "xcopa_id": {
+ "acc,none": 0.728,
+ "acc_stderr,none": 0.019920483209566072,
+ "alias": " - xcopa_id"
+ },
+ "xcopa_it": {
+ "acc,none": 0.746,
+ "acc_stderr,none": 0.01948659680164338,
+ "alias": " - xcopa_it"
+ },
+ "xcopa_qu": {
+ "acc,none": 0.514,
+ "acc_stderr,none": 0.022374298166353185,
+ "alias": " - xcopa_qu"
+ },
+ "xcopa_sw": {
+ "acc,none": 0.554,
+ "acc_stderr,none": 0.022252153078595897,
+ "alias": " - xcopa_sw"
+ },
+ "xcopa_ta": {
+ "acc,none": 0.582,
+ "acc_stderr,none": 0.022080014812228134,
+ "alias": " - xcopa_ta"
+ },
+ "xcopa_th": {
+ "acc,none": 0.584,
+ "acc_stderr,none": 0.022064943313928862,
+ "alias": " - xcopa_th"
+ },
+ "xcopa_tr": {
+ "acc,none": 0.63,
+ "acc_stderr,none": 0.02161328916516578,
+ "alias": " - xcopa_tr"
+ },
+ "xcopa_vi": {
+ "acc,none": 0.712,
+ "acc_stderr,none": 0.02027150383507522,
+ "alias": " - xcopa_vi"
+ },
+ "xcopa_zh": {
+ "acc,none": 0.698,
+ "acc_stderr,none": 0.02055326917420918,
+ "alias": " - xcopa_zh"
+ }
+ },
+ "groups": {
+ "xcopa": {
+ "acc,none": 0.6247272727272727,
+ "acc_stderr,none": 0.07076815037132106,
+ "alias": "xcopa"
+ }
+ },
+ "configs": {
+ "xcopa_et": {
+ "task": "xcopa_et",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "et",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'sest', 'effect': 'seetõttu'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ht": {
+ "task": "xcopa_ht",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ht",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'poukisa', 'effect': 'donk sa'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_id": {
+ "task": "xcopa_id",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "id",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'karena', 'effect': 'maka'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_it": {
+ "task": "xcopa_it",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "it",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'perché', 'effect': 'quindi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_qu": {
+ "task": "xcopa_qu",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "qu",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'imataq', 'effect': 'chaymi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_sw": {
+ "task": "xcopa_sw",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "sw",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ta": {
+ "task": "xcopa_ta",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ta",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_th": {
+ "task": "xcopa_th",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "th",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_tr": {
+ "task": "xcopa_tr",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "tr",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_vi": {
+ "task": "xcopa_vi",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "vi",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_zh": {
+ "task": "xcopa_zh",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "zh",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': '因为', 'effect': '所以'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "xcopa": "N/A",
+ "xcopa_et": 1.0,
+ "xcopa_ht": 1.0,
+ "xcopa_id": 1.0,
+ "xcopa_it": 1.0,
+ "xcopa_qu": 1.0,
+ "xcopa_sw": 1.0,
+ "xcopa_ta": 1.0,
+ "xcopa_th": 1.0,
+ "xcopa_tr": 1.0,
+ "xcopa_vi": 1.0,
+ "xcopa_zh": 1.0
+ },
+ "n-shot": {
+ "xcopa": 0,
+ "xcopa_et": 0,
+ "xcopa_ht": 0,
+ "xcopa_id": 0,
+ "xcopa_it": 0,
+ "xcopa_qu": 0,
+ "xcopa_sw": 0,
+ "xcopa_ta": 0,
+ "xcopa_th": 0,
+ "xcopa_tr": 0,
+ "xcopa_vi": 0,
+ "xcopa_zh": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2-blink_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
new file mode 100644
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+size 90260
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..9b1b22f25bbf94bbbabddbe1bec1de52725777e5
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+ "alias": "xnli"
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+ "alias": " - xnli_ar"
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+ "alias": " - xnli_bg"
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+ "acc_stderr,none": 0.01001740350857898,
+ "alias": " - xnli_de"
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+ "xnli_el": {
+ "acc,none": 0.38072289156626504,
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+ "alias": " - xnli_el"
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+ "acc_stderr,none": 0.00999977679318764,
+ "alias": " - xnli_en"
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+ "alias": " - xnli_es"
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+ "acc_stderr,none": 0.0100217495745559,
+ "alias": " - xnli_fr"
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+ "acc_stderr,none": 0.009932588282324245,
+ "alias": " - xnli_hi"
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+ "acc_stderr,none": 0.010013660629930818,
+ "alias": " - xnli_ru"
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+ "acc_stderr,none": 0.009769028875673286,
+ "alias": " - xnli_sw"
+ },
+ "xnli_th": {
+ "acc,none": 0.40843373493975904,
+ "acc_stderr,none": 0.00985258191903224,
+ "alias": " - xnli_th"
+ },
+ "xnli_tr": {
+ "acc,none": 0.4506024096385542,
+ "acc_stderr,none": 0.00997304277481168,
+ "alias": " - xnli_tr"
+ },
+ "xnli_ur": {
+ "acc,none": 0.41164658634538154,
+ "acc_stderr,none": 0.009864360821750344,
+ "alias": " - xnli_ur"
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+ "xnli_vi": {
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+ "acc_stderr,none": 0.009895812914052204,
+ "alias": " - xnli_vi"
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+ "xnli_zh": {
+ "acc,none": 0.3473895582329317,
+ "acc_stderr,none": 0.009543835409334902,
+ "alias": " - xnli_zh"
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+ "acc_stderr,none": 0.04961396343609649,
+ "alias": "xnli"
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+ "training_split": "train",
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+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", صحيح? نعم, \"+hypothesis,premise+\", صحيح? لذا, \"+hypothesis,premise+\", صحيح? رقم, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
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+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ "group": "xnli",
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+ "training_split": "train",
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+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", правилно? да, \"+hypothesis,premise+\", правилно? така, \"+hypothesis,premise+\", правилно? не, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
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+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", richtig? Ja, \"+hypothesis,premise+\", richtig? Auch, \"+hypothesis,premise+\", richtig? Nein, \"+hypothesis]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
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+ "xnli_el": {
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+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[premise+\", σωστός? Ναί, \"+hypothesis,premise+\", σωστός? Έτσι, \"+hypothesis,premise+\", σωστός? όχι, \"+hypothesis]}}",
+ "description": "",
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ "xnli_en": {
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+ "group": "xnli",
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+ "training_split": "train",
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+ "doc_to_text": "",
+ "doc_to_target": "label",
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+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "dataset_name": "fr",
+ "training_split": "train",
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+ "doc_to_text": "",
+ "doc_to_target": "label",
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+ "description": "",
+ "target_delimiter": " ",
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+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xwinograd_fr": {
+ "task": "xwinograd_fr",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "fr",
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+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
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+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ },
+ "xwinograd_jp": {
+ "task": "xwinograd_jp",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "jp",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
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+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xwinograd_pt": {
+ "task": "xwinograd_pt",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "pt",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
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+ "task": "xwinograd_ru",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "ru",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ "task": "xwinograd_zh",
+ "group": [
+ "xwinograd"
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+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "zh",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
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+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
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+ "git_hash": "8281e96"
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\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2-blink/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "target_delimiter": " ",
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+ "description": "",
+ "target_delimiter": " ",
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/ai2_arc/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "anli"
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+ "alias": " - anli_r1"
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+ "alias": " - anli_r3"
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+ "acc_stderr,none": 0.0176485793476215,
+ "alias": "anli"
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+ "group": [
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+ "dataset_path": "anli",
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+ "validation_split": "dev_r1",
+ "test_split": "test_r1",
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+ "metadata": {
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+}
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/anli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+ "doc_to_choice": [
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+ "description": "以下是关于农学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "group": "cmmlu",
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+ "dataset_name": "anatomy",
+ "test_split": "test",
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+ "doc_to_choice": [
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+ "description": "以下是关于解剖学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "task": "cmmlu_ancient_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "ancient_chinese",
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+ "doc_to_choice": [
+ "A",
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+ "C",
+ "D"
+ ],
+ "description": "以下是关于古汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "metadata": {
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+ "cmmlu_arts": {
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+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "arts",
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+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于艺术学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
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+ "metric_list": [
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
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+ },
+ "cmmlu_astronomy": {
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+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于天文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ "output_type": "multiple_choice",
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+ "metadata": {
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+ },
+ "cmmlu_business_ethics": {
+ "task": "cmmlu_business_ethics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于商业伦理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
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+ "higher_is_better": true
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
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+ },
+ "cmmlu_chinese_civil_service_exam": {
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+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_civil_service_exam",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国公务员考试的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
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+ {
+ "metric": "acc_norm",
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
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+ "should_decontaminate": false,
+ "metadata": {
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+ "cmmlu_chinese_driving_rule": {
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+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_driving_rule",
+ "test_split": "test",
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+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国驾驶规则的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ "higher_is_better": true
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+ "output_type": "multiple_choice",
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+ "metadata": {
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+ "dataset_name": "chinese_food_culture",
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+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
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+ "doc_to_choice": [
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+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国饮食文化的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "metric_list": [
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+ "aggregation": "mean",
+ "higher_is_better": true
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+ "metric": "acc_norm",
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+ "higher_is_better": true
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+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_foreign_policy": {
+ "task": "cmmlu_chinese_foreign_policy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国外交政策的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_history": {
+ "task": "cmmlu_chinese_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_literature": {
+ "task": "cmmlu_chinese_literature",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_literature",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_chinese_teacher_qualification": {
+ "task": "cmmlu_chinese_teacher_qualification",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "chinese_teacher_qualification",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中国教师资格的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_clinical_knowledge": {
+ "task": "cmmlu_clinical_knowledge",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于临床知识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_actuarial_science": {
+ "task": "cmmlu_college_actuarial_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_actuarial_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学精算学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_education": {
+ "task": "cmmlu_college_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_engineering_hydrology": {
+ "task": "cmmlu_college_engineering_hydrology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_engineering_hydrology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学工程水文学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_law": {
+ "task": "cmmlu_college_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学法律的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_mathematics": {
+ "task": "cmmlu_college_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medical_statistics": {
+ "task": "cmmlu_college_medical_statistics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medical_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学统计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_college_medicine": {
+ "task": "cmmlu_college_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于大学医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_science": {
+ "task": "cmmlu_computer_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_computer_security": {
+ "task": "cmmlu_computer_security",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于计算机安全的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_conceptual_physics": {
+ "task": "cmmlu_conceptual_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于概念物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_construction_project_management": {
+ "task": "cmmlu_construction_project_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "construction_project_management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于建设工程管理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_economics": {
+ "task": "cmmlu_economics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "economics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于经济学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_education": {
+ "task": "cmmlu_education",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "education",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于教育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_electrical_engineering": {
+ "task": "cmmlu_electrical_engineering",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于电气工程的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_chinese": {
+ "task": "cmmlu_elementary_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学语文的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_commonsense": {
+ "task": "cmmlu_elementary_commonsense",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_commonsense",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学常识的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_information_and_technology": {
+ "task": "cmmlu_elementary_information_and_technology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_information_and_technology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于小学信息技术的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_elementary_mathematics": {
+ "task": "cmmlu_elementary_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于初等数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_ethnology": {
+ "task": "cmmlu_ethnology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "ethnology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于民族学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_food_science": {
+ "task": "cmmlu_food_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "food_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于食品科学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_genetics": {
+ "task": "cmmlu_genetics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于遗传学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_global_facts": {
+ "task": "cmmlu_global_facts",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于全球事实的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_biology": {
+ "task": "cmmlu_high_school_biology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中生物的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_chemistry": {
+ "task": "cmmlu_high_school_chemistry",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中化学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_geography": {
+ "task": "cmmlu_high_school_geography",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中地理的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_mathematics": {
+ "task": "cmmlu_high_school_mathematics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中数学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_physics": {
+ "task": "cmmlu_high_school_physics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中物理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_high_school_politics": {
+ "task": "cmmlu_high_school_politics",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "high_school_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于高中政治的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_human_sexuality": {
+ "task": "cmmlu_human_sexuality",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于人类性行为的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_international_law": {
+ "task": "cmmlu_international_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于国际法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_journalism": {
+ "task": "cmmlu_journalism",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "journalism",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于新闻学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_jurisprudence": {
+ "task": "cmmlu_jurisprudence",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_legal_and_moral_basis": {
+ "task": "cmmlu_legal_and_moral_basis",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "legal_and_moral_basis",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于法律与道德基础的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_logical": {
+ "task": "cmmlu_logical",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "logical",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于逻辑学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_machine_learning": {
+ "task": "cmmlu_machine_learning",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于机器学习的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_management": {
+ "task": "cmmlu_management",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于管理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marketing": {
+ "task": "cmmlu_marketing",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于市场营销的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_marxist_theory": {
+ "task": "cmmlu_marxist_theory",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "marxist_theory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于马克思主义理论的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_modern_chinese": {
+ "task": "cmmlu_modern_chinese",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "modern_chinese",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于现代汉语的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_nutrition": {
+ "task": "cmmlu_nutrition",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于营养学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_philosophy": {
+ "task": "cmmlu_philosophy",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于哲学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_accounting": {
+ "task": "cmmlu_professional_accounting",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业会计的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_law": {
+ "task": "cmmlu_professional_law",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业法学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_medicine": {
+ "task": "cmmlu_professional_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业医学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_professional_psychology": {
+ "task": "cmmlu_professional_psychology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于专业心理学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_public_relations": {
+ "task": "cmmlu_public_relations",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于公共关系的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_security_study": {
+ "task": "cmmlu_security_study",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "security_study",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于安全研究的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sociology": {
+ "task": "cmmlu_sociology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于社会学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_sports_science": {
+ "task": "cmmlu_sports_science",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "sports_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于体育学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_traditional_chinese_medicine": {
+ "task": "cmmlu_traditional_chinese_medicine",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "traditional_chinese_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于中医中药的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_virology": {
+ "task": "cmmlu_virology",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于病毒学的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_world_history": {
+ "task": "cmmlu_world_history",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界历史的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
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+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "cmmlu_world_religions": {
+ "task": "cmmlu_world_religions",
+ "group": "cmmlu",
+ "dataset_path": "haonan-li/cmmlu",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{Question.strip()}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案:",
+ "doc_to_target": "{{['A', 'B', 'C', 'D'].index(Answer)}}",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "以下是关于世界宗教的单项选择题,请直接给出正确答案的选项。\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
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+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ }
+ },
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+ "config": {
+ "model": "hf",
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+ "results": {
+ "copa": {
+ "acc,none": 0.86,
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+ "alias": "copa"
+ }
+ },
+ "configs": {
+ "copa": {
+ "task": "copa",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "copa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n # Drop the period\n connector = {\n \"cause\": \"because\",\n \"effect\": \"therefore\",\n }[doc[\"question\"]]\n return doc[\"premise\"].strip()[:-1] + f\" {connector}\"\n",
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+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
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+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "copa": 1.0
+ },
+ "n-shot": {
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+ ],
+ "description": "",
+ "target_delimiter": " ",
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+ "metric_list": [
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+ "metadata": {
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+ "acc,none": 0.17592592592592593,
+ "acc_stderr,none": 0.025967420958258526
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+ "mmlu_machine_learning": {
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+ "alias": "mmlu"
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+ "configs": {
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+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ }
+ },
+ "versions": {
+ "mmlu": "N/A",
+ "mmlu_abstract_algebra": 0.0,
+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
+ "mmlu_college_computer_science": 0.0,
+ "mmlu_college_mathematics": 0.0,
+ "mmlu_college_medicine": 0.0,
+ "mmlu_college_physics": 0.0,
+ "mmlu_computer_security": 0.0,
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+ "task": "blimp_wh_vs_that_no_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_no_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap": {
+ "task": "blimp_wh_vs_that_with_gap",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "blimp_wh_vs_that_with_gap_long_distance": {
+ "task": "blimp_wh_vs_that_with_gap_long_distance",
+ "group": "blimp",
+ "dataset_path": "blimp",
+ "dataset_name": "wh_vs_that_with_gap_long_distance",
+ "validation_split": "train",
+ "doc_to_text": "",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{[sentence_good, sentence_bad]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{sentence_good}} {{sentence_bad}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "lambada_openai": {
+ "task": "lambada_openai",
+ "group": [
+ "lambada"
+ ],
+ "dataset_path": "EleutherAI/lambada_openai",
+ "dataset_name": "default",
+ "test_split": "test",
+ "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}",
+ "doc_to_target": "{{' '+text.split(' ')[-1]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "perplexity",
+ "aggregation": "perplexity",
+ "higher_is_better": false
+ },
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "loglikelihood",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{text}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "logiqa": {
+ "task": "logiqa",
+ "dataset_path": "EleutherAI/logiqa",
+ "dataset_name": "logiqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Passage: \n Question: \n Choices:\n A. \n B. \n C. \n D. \n Answer:\n \"\"\"\n choices = [\"a\", \"b\", \"c\", \"d\"]\n prompt = \"Passage: \" + doc[\"context\"] + \"\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\nChoices:\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"Answer:\"\n return prompt\n",
+ "doc_to_target": "def doc_to_target(doc) -> int:\n choices = [\"a\", \"b\", \"c\", \"d\"]\n return choices.index(doc[\"label\"].strip())\n",
+ "doc_to_choice": "{{options}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{context}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "mmlu_abstract_algebra": {
+ "task": "mmlu_abstract_algebra",
+ "task_alias": "abstract_algebra",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "abstract_algebra",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_anatomy": {
+ "task": "mmlu_anatomy",
+ "task_alias": "anatomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "anatomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about anatomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_astronomy": {
+ "task": "mmlu_astronomy",
+ "task_alias": "astronomy",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "astronomy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about astronomy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_business_ethics": {
+ "task": "mmlu_business_ethics",
+ "task_alias": "business_ethics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "business_ethics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about business ethics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_clinical_knowledge": {
+ "task": "mmlu_clinical_knowledge",
+ "task_alias": "clinical_knowledge",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "clinical_knowledge",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_biology": {
+ "task": "mmlu_college_biology",
+ "task_alias": "college_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_chemistry": {
+ "task": "mmlu_college_chemistry",
+ "task_alias": "college_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_computer_science": {
+ "task": "mmlu_college_computer_science",
+ "task_alias": "college_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_mathematics": {
+ "task": "mmlu_college_mathematics",
+ "task_alias": "college_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_medicine": {
+ "task": "mmlu_college_medicine",
+ "task_alias": "college_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_college_physics": {
+ "task": "mmlu_college_physics",
+ "task_alias": "college_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "college_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about college physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_computer_security": {
+ "task": "mmlu_computer_security",
+ "task_alias": "computer_security",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "computer_security",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about computer security.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_conceptual_physics": {
+ "task": "mmlu_conceptual_physics",
+ "task_alias": "conceptual_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "conceptual_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_econometrics": {
+ "task": "mmlu_econometrics",
+ "task_alias": "econometrics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "econometrics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about econometrics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_electrical_engineering": {
+ "task": "mmlu_electrical_engineering",
+ "task_alias": "electrical_engineering",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "electrical_engineering",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_elementary_mathematics": {
+ "task": "mmlu_elementary_mathematics",
+ "task_alias": "elementary_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "elementary_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_formal_logic": {
+ "task": "mmlu_formal_logic",
+ "task_alias": "formal_logic",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "formal_logic",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about formal logic.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_global_facts": {
+ "task": "mmlu_global_facts",
+ "task_alias": "global_facts",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "global_facts",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about global facts.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_biology": {
+ "task": "mmlu_high_school_biology",
+ "task_alias": "high_school_biology",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_biology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school biology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_chemistry": {
+ "task": "mmlu_high_school_chemistry",
+ "task_alias": "high_school_chemistry",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_chemistry",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_computer_science": {
+ "task": "mmlu_high_school_computer_science",
+ "task_alias": "high_school_computer_science",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_computer_science",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_european_history": {
+ "task": "mmlu_high_school_european_history",
+ "task_alias": "high_school_european_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_european_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school european history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_geography": {
+ "task": "mmlu_high_school_geography",
+ "task_alias": "high_school_geography",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_geography",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school geography.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_government_and_politics": {
+ "task": "mmlu_high_school_government_and_politics",
+ "task_alias": "high_school_government_and_politics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_government_and_politics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_macroeconomics": {
+ "task": "mmlu_high_school_macroeconomics",
+ "task_alias": "high_school_macroeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_macroeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_mathematics": {
+ "task": "mmlu_high_school_mathematics",
+ "task_alias": "high_school_mathematics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_mathematics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_microeconomics": {
+ "task": "mmlu_high_school_microeconomics",
+ "task_alias": "high_school_microeconomics",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_microeconomics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_physics": {
+ "task": "mmlu_high_school_physics",
+ "task_alias": "high_school_physics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_physics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school physics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_psychology": {
+ "task": "mmlu_high_school_psychology",
+ "task_alias": "high_school_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_statistics": {
+ "task": "mmlu_high_school_statistics",
+ "task_alias": "high_school_statistics",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_statistics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_us_history": {
+ "task": "mmlu_high_school_us_history",
+ "task_alias": "high_school_us_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_us_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school us history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_high_school_world_history": {
+ "task": "mmlu_high_school_world_history",
+ "task_alias": "high_school_world_history",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "high_school_world_history",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about high school world history.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_aging": {
+ "task": "mmlu_human_aging",
+ "task_alias": "human_aging",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_aging",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human aging.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_human_sexuality": {
+ "task": "mmlu_human_sexuality",
+ "task_alias": "human_sexuality",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "human_sexuality",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_international_law": {
+ "task": "mmlu_international_law",
+ "task_alias": "international_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "international_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about international law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_jurisprudence": {
+ "task": "mmlu_jurisprudence",
+ "task_alias": "jurisprudence",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "jurisprudence",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_logical_fallacies": {
+ "task": "mmlu_logical_fallacies",
+ "task_alias": "logical_fallacies",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "logical_fallacies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_machine_learning": {
+ "task": "mmlu_machine_learning",
+ "task_alias": "machine_learning",
+ "group": "mmlu_stem",
+ "group_alias": "stem",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "machine_learning",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about machine learning.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_management": {
+ "task": "mmlu_management",
+ "task_alias": "management",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "management",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about management.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_marketing": {
+ "task": "mmlu_marketing",
+ "task_alias": "marketing",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "marketing",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about marketing.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_medical_genetics": {
+ "task": "mmlu_medical_genetics",
+ "task_alias": "medical_genetics",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "medical_genetics",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_miscellaneous": {
+ "task": "mmlu_miscellaneous",
+ "task_alias": "miscellaneous",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "miscellaneous",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_disputes": {
+ "task": "mmlu_moral_disputes",
+ "task_alias": "moral_disputes",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_disputes",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_moral_scenarios": {
+ "task": "mmlu_moral_scenarios",
+ "task_alias": "moral_scenarios",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "moral_scenarios",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_nutrition": {
+ "task": "mmlu_nutrition",
+ "task_alias": "nutrition",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "nutrition",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about nutrition.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_philosophy": {
+ "task": "mmlu_philosophy",
+ "task_alias": "philosophy",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "philosophy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about philosophy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_prehistory": {
+ "task": "mmlu_prehistory",
+ "task_alias": "prehistory",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "prehistory",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about prehistory.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_accounting": {
+ "task": "mmlu_professional_accounting",
+ "task_alias": "professional_accounting",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_accounting",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_law": {
+ "task": "mmlu_professional_law",
+ "task_alias": "professional_law",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_law",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional law.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_medicine": {
+ "task": "mmlu_professional_medicine",
+ "task_alias": "professional_medicine",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_medicine",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_professional_psychology": {
+ "task": "mmlu_professional_psychology",
+ "task_alias": "professional_psychology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "professional_psychology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_public_relations": {
+ "task": "mmlu_public_relations",
+ "task_alias": "public_relations",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "public_relations",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about public relations.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_security_studies": {
+ "task": "mmlu_security_studies",
+ "task_alias": "security_studies",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "security_studies",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about security studies.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_sociology": {
+ "task": "mmlu_sociology",
+ "task_alias": "sociology",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "sociology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about sociology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_us_foreign_policy": {
+ "task": "mmlu_us_foreign_policy",
+ "task_alias": "us_foreign_policy",
+ "group": "mmlu_social_sciences",
+ "group_alias": "social_sciences",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "us_foreign_policy",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_virology": {
+ "task": "mmlu_virology",
+ "task_alias": "virology",
+ "group": "mmlu_other",
+ "group_alias": "other",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "virology",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about virology.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "mmlu_world_religions": {
+ "task": "mmlu_world_religions",
+ "task_alias": "world_religions",
+ "group": "mmlu_humanities",
+ "group_alias": "humanities",
+ "dataset_path": "hails/mmlu_no_train",
+ "dataset_name": "world_religions",
+ "test_split": "test",
+ "fewshot_split": "dev",
+ "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:",
+ "doc_to_target": "answer",
+ "doc_to_choice": [
+ "A",
+ "B",
+ "C",
+ "D"
+ ],
+ "description": "The following are multiple choice questions (with answers) about world religions.\n\n",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "fewshot_config": {
+ "sampler": "first_n"
+ },
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 0.0
+ }
+ },
+ "piqa": {
+ "task": "piqa",
+ "dataset_path": "piqa",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "Question: {{goal}}\nAnswer:",
+ "doc_to_target": "label",
+ "doc_to_choice": "{{[sol1, sol2]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "goal",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "sciq": {
+ "task": "sciq",
+ "dataset_path": "sciq",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "{{support.lstrip()}}\nQuestion: {{question}}\nAnswer:",
+ "doc_to_target": 3,
+ "doc_to_choice": "{{[distractor1, distractor2, distractor3, correct_answer]}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "acc_norm",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{support}} {{question}}",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wikitext": {
+ "task": "wikitext",
+ "dataset_path": "EleutherAI/wikitext_document_level",
+ "dataset_name": "wikitext-2-raw-v1",
+ "training_split": "train",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "",
+ "doc_to_target": "def wikitext_detokenizer(doc):\n string = doc[\"page\"]\n # contractions\n string = string.replace(\"s '\", \"s'\")\n string = re.sub(r\"/' [0-9]/\", r\"/'[0-9]/\", string)\n # number separators\n string = string.replace(\" @-@ \", \"-\")\n string = string.replace(\" @,@ \", \",\")\n string = string.replace(\" @.@ \", \".\")\n # punctuation\n string = string.replace(\" : \", \": \")\n string = string.replace(\" ; \", \"; \")\n string = string.replace(\" . \", \". \")\n string = string.replace(\" ! \", \"! \")\n string = string.replace(\" ? \", \"? \")\n string = string.replace(\" , \", \", \")\n # double brackets\n string = re.sub(r\"\\(\\s*([^\\)]*?)\\s*\\)\", r\"(\\1)\", string)\n string = re.sub(r\"\\[\\s*([^\\]]*?)\\s*\\]\", r\"[\\1]\", string)\n string = re.sub(r\"{\\s*([^}]*?)\\s*}\", r\"{\\1}\", string)\n string = re.sub(r\"\\\"\\s*([^\\\"]*?)\\s*\\\"\", r'\"\\1\"', string)\n string = re.sub(r\"'\\s*([^']*?)\\s*'\", r\"'\\1'\", string)\n # miscellaneous\n string = string.replace(\"= = = =\", \"====\")\n string = string.replace(\"= = =\", \"===\")\n string = string.replace(\"= =\", \"==\")\n string = string.replace(\" \" + chr(176) + \" \", chr(176))\n string = string.replace(\" \\n\", \"\\n\")\n string = string.replace(\"\\n \", \"\\n\")\n string = string.replace(\" N \", \" 1 \")\n string = string.replace(\" 's\", \"'s\")\n\n return string\n",
+ "process_results": "def process_results(doc, results):\n (loglikelihood,) = results\n # IMPORTANT: wikitext counts number of words in *original doc before detokenization*\n _words = len(re.split(r\"\\s+\", doc[\"page\"]))\n _bytes = len(doc[\"page\"].encode(\"utf-8\"))\n return {\n \"word_perplexity\": (loglikelihood, _words),\n \"byte_perplexity\": (loglikelihood, _bytes),\n \"bits_per_byte\": (loglikelihood, _bytes),\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "word_perplexity"
+ },
+ {
+ "metric": "byte_perplexity"
+ },
+ {
+ "metric": "bits_per_byte"
+ }
+ ],
+ "output_type": "loglikelihood_rolling",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "{{page}}",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "wsc": {
+ "task": "wsc",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "wsc.fixed",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def default_doc_to_text(x):\n raw_passage = x[\"text\"]\n # NOTE: HuggingFace span indices are word-based not character-based.\n pre = \" \".join(raw_passage.split()[: x[\"span2_index\"]])\n post = raw_passage[len(pre) + len(x[\"span2_text\"]) + 1 :]\n passage = general_detokenize(pre + \" *{}*\".format(x[\"span2_text\"]) + post)\n noun = x[\"span1_text\"]\n pronoun = x[\"span2_text\"]\n text = (\n f\"Passage: {passage}\\n\"\n + f'Question: In the passage above, does the pronoun \"*{pronoun}*\" refer to \"*{noun}*\"?\\n'\n + \"Answer:\"\n )\n return text\n",
+ "doc_to_target": "label",
+ "doc_to_choice": [
+ "no",
+ "yes"
+ ],
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "ai2_arc": "N/A",
+ "arc_challenge": 1.0,
+ "arc_easy": 1.0,
+ "blimp": "N/A",
+ "blimp_adjunct_island": 1.0,
+ "blimp_anaphor_gender_agreement": 1.0,
+ "blimp_anaphor_number_agreement": 1.0,
+ "blimp_animate_subject_passive": 1.0,
+ "blimp_animate_subject_trans": 1.0,
+ "blimp_causative": 1.0,
+ "blimp_complex_NP_island": 1.0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 1.0,
+ "blimp_coordinate_structure_constraint_object_extraction": 1.0,
+ "blimp_determiner_noun_agreement_1": 1.0,
+ "blimp_determiner_noun_agreement_2": 1.0,
+ "blimp_determiner_noun_agreement_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 1.0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 1.0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 1.0,
+ "blimp_distractor_agreement_relational_noun": 1.0,
+ "blimp_distractor_agreement_relative_clause": 1.0,
+ "blimp_drop_argument": 1.0,
+ "blimp_ellipsis_n_bar_1": 1.0,
+ "blimp_ellipsis_n_bar_2": 1.0,
+ "blimp_existential_there_object_raising": 1.0,
+ "blimp_existential_there_quantifiers_1": 1.0,
+ "blimp_existential_there_quantifiers_2": 1.0,
+ "blimp_existential_there_subject_raising": 1.0,
+ "blimp_expletive_it_object_raising": 1.0,
+ "blimp_inchoative": 1.0,
+ "blimp_intransitive": 1.0,
+ "blimp_irregular_past_participle_adjectives": 1.0,
+ "blimp_irregular_past_participle_verbs": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_left_branch_island_echo_question": 1.0,
+ "blimp_left_branch_island_simple_question": 1.0,
+ "blimp_matrix_question_npi_licensor_present": 1.0,
+ "blimp_npi_present_1": 1.0,
+ "blimp_npi_present_2": 1.0,
+ "blimp_only_npi_licensor_present": 1.0,
+ "blimp_only_npi_scope": 1.0,
+ "blimp_passive_1": 1.0,
+ "blimp_passive_2": 1.0,
+ "blimp_principle_A_c_command": 1.0,
+ "blimp_principle_A_case_1": 1.0,
+ "blimp_principle_A_case_2": 1.0,
+ "blimp_principle_A_domain_1": 1.0,
+ "blimp_principle_A_domain_2": 1.0,
+ "blimp_principle_A_domain_3": 1.0,
+ "blimp_principle_A_reconstruction": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_1": 1.0,
+ "blimp_regular_plural_subject_verb_agreement_2": 1.0,
+ "blimp_sentential_negation_npi_licensor_present": 1.0,
+ "blimp_sentential_negation_npi_scope": 1.0,
+ "blimp_sentential_subject_island": 1.0,
+ "blimp_superlative_quantifiers_1": 1.0,
+ "blimp_superlative_quantifiers_2": 1.0,
+ "blimp_tough_vs_raising_1": 1.0,
+ "blimp_tough_vs_raising_2": 1.0,
+ "blimp_transitive": 1.0,
+ "blimp_wh_island": 1.0,
+ "blimp_wh_questions_object_gap": 1.0,
+ "blimp_wh_questions_subject_gap": 1.0,
+ "blimp_wh_questions_subject_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_no_gap": 1.0,
+ "blimp_wh_vs_that_no_gap_long_distance": 1.0,
+ "blimp_wh_vs_that_with_gap": 1.0,
+ "blimp_wh_vs_that_with_gap_long_distance": 1.0,
+ "lambada_openai": 1.0,
+ "logiqa": 1.0,
+ "mmlu": "N/A",
+ "mmlu_abstract_algebra": 0.0,
+ "mmlu_anatomy": 0.0,
+ "mmlu_astronomy": 0.0,
+ "mmlu_business_ethics": 0.0,
+ "mmlu_clinical_knowledge": 0.0,
+ "mmlu_college_biology": 0.0,
+ "mmlu_college_chemistry": 0.0,
+ "mmlu_college_computer_science": 0.0,
+ "mmlu_college_mathematics": 0.0,
+ "mmlu_college_medicine": 0.0,
+ "mmlu_college_physics": 0.0,
+ "mmlu_computer_security": 0.0,
+ "mmlu_conceptual_physics": 0.0,
+ "mmlu_econometrics": 0.0,
+ "mmlu_electrical_engineering": 0.0,
+ "mmlu_elementary_mathematics": 0.0,
+ "mmlu_formal_logic": 0.0,
+ "mmlu_global_facts": 0.0,
+ "mmlu_high_school_biology": 0.0,
+ "mmlu_high_school_chemistry": 0.0,
+ "mmlu_high_school_computer_science": 0.0,
+ "mmlu_high_school_european_history": 0.0,
+ "mmlu_high_school_geography": 0.0,
+ "mmlu_high_school_government_and_politics": 0.0,
+ "mmlu_high_school_macroeconomics": 0.0,
+ "mmlu_high_school_mathematics": 0.0,
+ "mmlu_high_school_microeconomics": 0.0,
+ "mmlu_high_school_physics": 0.0,
+ "mmlu_high_school_psychology": 0.0,
+ "mmlu_high_school_statistics": 0.0,
+ "mmlu_high_school_us_history": 0.0,
+ "mmlu_high_school_world_history": 0.0,
+ "mmlu_human_aging": 0.0,
+ "mmlu_human_sexuality": 0.0,
+ "mmlu_humanities": "N/A",
+ "mmlu_international_law": 0.0,
+ "mmlu_jurisprudence": 0.0,
+ "mmlu_logical_fallacies": 0.0,
+ "mmlu_machine_learning": 0.0,
+ "mmlu_management": 0.0,
+ "mmlu_marketing": 0.0,
+ "mmlu_medical_genetics": 0.0,
+ "mmlu_miscellaneous": 0.0,
+ "mmlu_moral_disputes": 0.0,
+ "mmlu_moral_scenarios": 0.0,
+ "mmlu_nutrition": 0.0,
+ "mmlu_other": "N/A",
+ "mmlu_philosophy": 0.0,
+ "mmlu_prehistory": 0.0,
+ "mmlu_professional_accounting": 0.0,
+ "mmlu_professional_law": 0.0,
+ "mmlu_professional_medicine": 0.0,
+ "mmlu_professional_psychology": 0.0,
+ "mmlu_public_relations": 0.0,
+ "mmlu_security_studies": 0.0,
+ "mmlu_social_sciences": "N/A",
+ "mmlu_sociology": 0.0,
+ "mmlu_stem": "N/A",
+ "mmlu_us_foreign_policy": 0.0,
+ "mmlu_virology": 0.0,
+ "mmlu_world_religions": 0.0,
+ "piqa": 1.0,
+ "pythia": "N/A",
+ "sciq": 1.0,
+ "wikitext": 2.0,
+ "winogrande": 1.0,
+ "wsc": 1.0
+ },
+ "n-shot": {
+ "ai2_arc": 0,
+ "arc_challenge": 0,
+ "arc_easy": 0,
+ "blimp": 0,
+ "blimp_adjunct_island": 0,
+ "blimp_anaphor_gender_agreement": 0,
+ "blimp_anaphor_number_agreement": 0,
+ "blimp_animate_subject_passive": 0,
+ "blimp_animate_subject_trans": 0,
+ "blimp_causative": 0,
+ "blimp_complex_NP_island": 0,
+ "blimp_coordinate_structure_constraint_complex_left_branch": 0,
+ "blimp_coordinate_structure_constraint_object_extraction": 0,
+ "blimp_determiner_noun_agreement_1": 0,
+ "blimp_determiner_noun_agreement_2": 0,
+ "blimp_determiner_noun_agreement_irregular_1": 0,
+ "blimp_determiner_noun_agreement_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_2": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_1": 0,
+ "blimp_determiner_noun_agreement_with_adj_irregular_2": 0,
+ "blimp_determiner_noun_agreement_with_adjective_1": 0,
+ "blimp_distractor_agreement_relational_noun": 0,
+ "blimp_distractor_agreement_relative_clause": 0,
+ "blimp_drop_argument": 0,
+ "blimp_ellipsis_n_bar_1": 0,
+ "blimp_ellipsis_n_bar_2": 0,
+ "blimp_existential_there_object_raising": 0,
+ "blimp_existential_there_quantifiers_1": 0,
+ "blimp_existential_there_quantifiers_2": 0,
+ "blimp_existential_there_subject_raising": 0,
+ "blimp_expletive_it_object_raising": 0,
+ "blimp_inchoative": 0,
+ "blimp_intransitive": 0,
+ "blimp_irregular_past_participle_adjectives": 0,
+ "blimp_irregular_past_participle_verbs": 0,
+ "blimp_irregular_plural_subject_verb_agreement_1": 0,
+ "blimp_irregular_plural_subject_verb_agreement_2": 0,
+ "blimp_left_branch_island_echo_question": 0,
+ "blimp_left_branch_island_simple_question": 0,
+ "blimp_matrix_question_npi_licensor_present": 0,
+ "blimp_npi_present_1": 0,
+ "blimp_npi_present_2": 0,
+ "blimp_only_npi_licensor_present": 0,
+ "blimp_only_npi_scope": 0,
+ "blimp_passive_1": 0,
+ "blimp_passive_2": 0,
+ "blimp_principle_A_c_command": 0,
+ "blimp_principle_A_case_1": 0,
+ "blimp_principle_A_case_2": 0,
+ "blimp_principle_A_domain_1": 0,
+ "blimp_principle_A_domain_2": 0,
+ "blimp_principle_A_domain_3": 0,
+ "blimp_principle_A_reconstruction": 0,
+ "blimp_regular_plural_subject_verb_agreement_1": 0,
+ "blimp_regular_plural_subject_verb_agreement_2": 0,
+ "blimp_sentential_negation_npi_licensor_present": 0,
+ "blimp_sentential_negation_npi_scope": 0,
+ "blimp_sentential_subject_island": 0,
+ "blimp_superlative_quantifiers_1": 0,
+ "blimp_superlative_quantifiers_2": 0,
+ "blimp_tough_vs_raising_1": 0,
+ "blimp_tough_vs_raising_2": 0,
+ "blimp_transitive": 0,
+ "blimp_wh_island": 0,
+ "blimp_wh_questions_object_gap": 0,
+ "blimp_wh_questions_subject_gap": 0,
+ "blimp_wh_questions_subject_gap_long_distance": 0,
+ "blimp_wh_vs_that_no_gap": 0,
+ "blimp_wh_vs_that_no_gap_long_distance": 0,
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/pythia/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/pythia/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "em,none": 0.2523,
+ "em_stderr,none": 0.004343542061010362,
+ "alias": "record"
+ }
+ },
+ "configs": {
+ "record": {
+ "task": "record",
+ "group": [
+ "super-glue-lm-eval-v1"
+ ],
+ "dataset_path": "super_glue",
+ "dataset_name": "record",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n initial_text, *highlights = doc[\"passage\"].strip().split(\"\\n@highlight\\n\")\n text = initial_text + \"\\n\\n\"\n for highlight in highlights:\n text += f\" - {highlight}.\\n\"\n return text\n",
+ "doc_to_target": "{{answers}}",
+ "doc_to_choice": "{{entities}}",
+ "process_results": "def process_results(doc, results):\n # ReCoRD's evaluation is actually deceptively simple:\n # - Pick the maximum likelihood prediction entity\n # - Evaluate the accuracy and token F1 PER EXAMPLE\n # - Average over all examples\n max_idx = np.argmax(np.array([result[0] for result in results]))\n\n prediction = doc[\"entities\"][max_idx]\n gold_label_set = doc[\"answers\"]\n f1 = metric_max_over_ground_truths(\n squad_metrics.compute_f1, prediction, gold_label_set\n )\n em = metric_max_over_ground_truths(\n squad_metrics.compute_exact, prediction, gold_label_set\n )\n\n return {\n \"f1\": f1,\n \"em\": em,\n }\n",
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+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
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+ "higher_is_better": true,
+ "aggregation": "mean"
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+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
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+ }
+ },
+ "versions": {
+ "record": 1.0
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+ "n-shot": {
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+ "model": "hf",
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+ "batch_size": "auto",
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/record/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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+ "alias": "sciq"
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+ "versions": {
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diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/sciq/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+ "alias": " - truthfulqa_gen"
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+ "truthfulqa_mc1": {
+ "acc,none": 0.25458996328029376,
+ "acc_stderr,none": 0.015250117079156507,
+ "alias": " - truthfulqa_mc1"
+ },
+ "truthfulqa_mc2": {
+ "acc,none": 0.4060039567029496,
+ "acc_stderr,none": 0.014334452088177841,
+ "alias": " - truthfulqa_mc2"
+ }
+ },
+ "groups": {
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+ "acc_stderr,none": 0.001652651966553619,
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+ "rougeL_diff,none": -5.8769273011964565,
+ "rougeL_diff_stderr,none": 1.098816821965796,
+ "alias": "truthfulqa"
+ }
+ },
+ "configs": {
+ "truthfulqa_gen": {
+ "task": "truthfulqa_gen",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "generation",
+ "validation_split": "validation",
+ "process_docs": "def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset:\n return dataset.map(preprocess_function)\n",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question}}",
+ "doc_to_target": " ",
+ "process_results": "def process_results_gen(doc, results):\n completion = results[0]\n true_refs, false_refs = doc[\"correct_answers\"], doc[\"incorrect_answers\"]\n all_refs = true_refs + false_refs\n\n # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures.\n\n # # BLEURT\n # bleurt_scores_true = self.bleurt.compute(\n # predictions=[completion] * len(true_refs), references=true_refs\n # )[\"scores\"]\n # bleurt_scores_false = self.bleurt.compute(\n # predictions=[completion] * len(false_refs), references=false_refs\n # )[\"scores\"]\n # bleurt_correct = max(bleurt_scores_true)\n # bleurt_incorrect = max(bleurt_scores_false)\n # bleurt_max = bleurt_correct\n # bleurt_diff = bleurt_correct - bleurt_incorrect\n # bleurt_acc = int(bleurt_correct > bleurt_incorrect)\n\n # BLEU\n bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs]\n bleu_correct = np.nanmax(bleu_scores[: len(true_refs)])\n bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :])\n bleu_max = bleu_correct\n bleu_diff = bleu_correct - bleu_incorrect\n bleu_acc = int(bleu_correct > bleu_incorrect)\n\n # ROUGE-N\n rouge_scores = [rouge([ref], [completion]) for ref in all_refs]\n # ROUGE-1\n rouge1_scores = [score[\"rouge1\"] for score in rouge_scores]\n rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)])\n rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :])\n rouge1_max = rouge1_correct\n rouge1_diff = rouge1_correct - rouge1_incorrect\n rouge1_acc = int(rouge1_correct > rouge1_incorrect)\n # ROUGE-2\n rouge2_scores = [score[\"rouge2\"] for score in rouge_scores]\n rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)])\n rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :])\n rouge2_max = rouge2_correct\n rouge2_diff = rouge2_correct - rouge2_incorrect\n rouge2_acc = int(rouge2_correct > rouge2_incorrect)\n # ROUGE-L\n rougeL_scores = [score[\"rougeLsum\"] for score in rouge_scores]\n rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)])\n rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :])\n rougeL_max = rougeL_correct\n rougeL_diff = rougeL_correct - rougeL_incorrect\n rougeL_acc = int(rougeL_correct > rougeL_incorrect)\n\n return {\n # \"bleurt_max\": bleurt_max,\n # \"bleurt_acc\": bleurt_acc,\n # \"bleurt_diff\": bleurt_diff,\n \"bleu_max\": bleu_max,\n \"bleu_acc\": bleu_acc,\n \"bleu_diff\": bleu_diff,\n \"rouge1_max\": rouge1_max,\n \"rouge1_acc\": rouge1_acc,\n \"rouge1_diff\": rouge1_diff,\n \"rouge2_max\": rouge2_max,\n \"rouge2_acc\": rouge2_acc,\n \"rouge2_diff\": rouge2_diff,\n \"rougeL_max\": rougeL_max,\n \"rougeL_acc\": rougeL_acc,\n \"rougeL_diff\": rougeL_diff,\n }\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "bleu_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "bleu_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge1_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rouge2_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_max",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ },
+ {
+ "metric": "rougeL_diff",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "generate_until",
+ "generation_kwargs": {
+ "until": [
+ "\n\n"
+ ],
+ "do_sample": false
+ },
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 3.0
+ }
+ },
+ "truthfulqa_mc1": {
+ "task": "truthfulqa_mc1",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc1_targets.choices}}",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ },
+ "truthfulqa_mc2": {
+ "task": "truthfulqa_mc2",
+ "group": [
+ "truthfulqa"
+ ],
+ "dataset_path": "truthful_qa",
+ "dataset_name": "multiple_choice",
+ "validation_split": "validation",
+ "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}",
+ "doc_to_target": 0,
+ "doc_to_choice": "{{mc2_targets.choices}}",
+ "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "num_fewshot": 0,
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "question",
+ "metadata": {
+ "version": 2.0
+ }
+ }
+ },
+ "versions": {
+ "truthfulqa": "N/A",
+ "truthfulqa_gen": 3.0,
+ "truthfulqa_mc1": 2.0,
+ "truthfulqa_mc2": 2.0
+ },
+ "n-shot": {
+ "truthfulqa": 0,
+ "truthfulqa_gen": 0,
+ "truthfulqa_mc1": 0,
+ "truthfulqa_mc2": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/truthfulqa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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+version https://git-lfs.github.com/spec/v1
+oid sha256:93d3a95e08ebb1e180b5fbc57590b3b844d0c83c01df2f7fa1e92ffb1cdce4c7
+size 599522
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
new file mode 100644
index 0000000000000000000000000000000000000000..a67c7e8adea7d43d4917d7bb52c1d2f9e79da4c6
--- /dev/null
+++ b/lm-eval-output/rwkv-x-dev/r3-testchunk2/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
@@ -0,0 +1,58 @@
+{
+ "results": {
+ "winogrande": {
+ "acc,none": 0.675611681136543,
+ "acc_stderr,none": 0.013157225726641646,
+ "alias": "winogrande"
+ }
+ },
+ "configs": {
+ "winogrande": {
+ "task": "winogrande",
+ "dataset_path": "winogrande",
+ "dataset_name": "winogrande_xl",
+ "training_split": "train",
+ "validation_split": "validation",
+ "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
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+ "metric_list": [
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+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": true,
+ "doc_to_decontamination_query": "sentence",
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "winogrande": 1.0
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+ "n-shot": {
+ "winogrande": 0
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+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
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+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
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+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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index 0000000000000000000000000000000000000000..c8192c68be2a22e86cd0642463c01739566cd640
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+size 8883
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/rwkv-x-dev/r3-testchunk2/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json
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index 0000000000000000000000000000000000000000..44c00fbcedbd040619fc427a9d3b30ccbb91330c
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+{
+ "results": {
+ "xcopa": {
+ "acc,none": 0.6218181818181818,
+ "acc_stderr,none": 0.0711251373879857,
+ "alias": "xcopa"
+ },
+ "xcopa_et": {
+ "acc,none": 0.602,
+ "acc_stderr,none": 0.02191237788577997,
+ "alias": " - xcopa_et"
+ },
+ "xcopa_ht": {
+ "acc,none": 0.518,
+ "acc_stderr,none": 0.02236856511738799,
+ "alias": " - xcopa_ht"
+ },
+ "xcopa_id": {
+ "acc,none": 0.724,
+ "acc_stderr,none": 0.02001121929807353,
+ "alias": " - xcopa_id"
+ },
+ "xcopa_it": {
+ "acc,none": 0.728,
+ "acc_stderr,none": 0.01992048320956607,
+ "alias": " - xcopa_it"
+ },
+ "xcopa_qu": {
+ "acc,none": 0.508,
+ "acc_stderr,none": 0.022380208834928035,
+ "alias": " - xcopa_qu"
+ },
+ "xcopa_sw": {
+ "acc,none": 0.544,
+ "acc_stderr,none": 0.022296238348407053,
+ "alias": " - xcopa_sw"
+ },
+ "xcopa_ta": {
+ "acc,none": 0.578,
+ "acc_stderr,none": 0.022109039310618552,
+ "alias": " - xcopa_ta"
+ },
+ "xcopa_th": {
+ "acc,none": 0.578,
+ "acc_stderr,none": 0.022109039310618552,
+ "alias": " - xcopa_th"
+ },
+ "xcopa_tr": {
+ "acc,none": 0.65,
+ "acc_stderr,none": 0.021352091786223104,
+ "alias": " - xcopa_tr"
+ },
+ "xcopa_vi": {
+ "acc,none": 0.708,
+ "acc_stderr,none": 0.02035437548053008,
+ "alias": " - xcopa_vi"
+ },
+ "xcopa_zh": {
+ "acc,none": 0.702,
+ "acc_stderr,none": 0.020475118092988978,
+ "alias": " - xcopa_zh"
+ }
+ },
+ "groups": {
+ "xcopa": {
+ "acc,none": 0.6218181818181818,
+ "acc_stderr,none": 0.0711251373879857,
+ "alias": "xcopa"
+ }
+ },
+ "configs": {
+ "xcopa_et": {
+ "task": "xcopa_et",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "et",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'sest', 'effect': 'seetõttu'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ht": {
+ "task": "xcopa_ht",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ht",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'poukisa', 'effect': 'donk sa'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_id": {
+ "task": "xcopa_id",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "id",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'karena', 'effect': 'maka'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_it": {
+ "task": "xcopa_it",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "it",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'perché', 'effect': 'quindi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_qu": {
+ "task": "xcopa_qu",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "qu",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'imataq', 'effect': 'chaymi'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_sw": {
+ "task": "xcopa_sw",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "sw",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_ta": {
+ "task": "xcopa_ta",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "ta",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_th": {
+ "task": "xcopa_th",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "th",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_tr": {
+ "task": "xcopa_tr",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "tr",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_vi": {
+ "task": "xcopa_vi",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "vi",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc"
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xcopa_zh": {
+ "task": "xcopa_zh",
+ "group": "xcopa",
+ "dataset_path": "xcopa",
+ "dataset_name": "zh",
+ "validation_split": "validation",
+ "test_split": "test",
+ "doc_to_text": "functools.partial(, connector={'cause': '因为', 'effect': '所以'})",
+ "doc_to_target": "label",
+ "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
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+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "xcopa": "N/A",
+ "xcopa_et": 1.0,
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+ "xcopa_id": 1.0,
+ "xcopa_it": 1.0,
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+ "xcopa_th": 1.0,
+ "xcopa_tr": 1.0,
+ "xcopa_vi": 1.0,
+ "xcopa_zh": 1.0
+ },
+ "n-shot": {
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+ "xcopa_zh": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
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+ "acc,none": 0.7658730158730159,
+ "acc_stderr,none": 0.0188807884850783,
+ "alias": " - xwinograd_zh"
+ }
+ },
+ "groups": {
+ "xwinograd": {
+ "acc,none": 0.8035513598561475,
+ "acc_stderr,none": 0.035442329439520394,
+ "alias": "xwinograd"
+ }
+ },
+ "configs": {
+ "xwinograd_en": {
+ "task": "xwinograd_en",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "en",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xwinograd_fr": {
+ "task": "xwinograd_fr",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "fr",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xwinograd_jp": {
+ "task": "xwinograd_jp",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "jp",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xwinograd_pt": {
+ "task": "xwinograd_pt",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "pt",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xwinograd_ru": {
+ "task": "xwinograd_ru",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "ru",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ },
+ "xwinograd_zh": {
+ "task": "xwinograd_zh",
+ "group": [
+ "xwinograd"
+ ],
+ "dataset_path": "Muennighoff/xwinograd",
+ "dataset_name": "zh",
+ "test_split": "test",
+ "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
+ "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
+ "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
+ "description": "",
+ "target_delimiter": " ",
+ "fewshot_delimiter": "\n\n",
+ "metric_list": [
+ {
+ "metric": "acc",
+ "aggregation": "mean",
+ "higher_is_better": true
+ }
+ ],
+ "output_type": "multiple_choice",
+ "repeats": 1,
+ "should_decontaminate": false,
+ "metadata": {
+ "version": 1.0
+ }
+ }
+ },
+ "versions": {
+ "xwinograd": "N/A",
+ "xwinograd_en": 1.0,
+ "xwinograd_fr": 1.0,
+ "xwinograd_jp": 1.0,
+ "xwinograd_pt": 1.0,
+ "xwinograd_ru": 1.0,
+ "xwinograd_zh": 1.0
+ },
+ "n-shot": {
+ "xwinograd": 0,
+ "xwinograd_en": 0,
+ "xwinograd_fr": 0,
+ "xwinograd_jp": 0,
+ "xwinograd_pt": 0,
+ "xwinograd_ru": 0,
+ "xwinograd_zh": 0
+ },
+ "config": {
+ "model": "hf",
+ "model_args": "pretrained=./rwkv-x-dev/r3-testchunk2_pth,dtype=bfloat16,trust_remote_code=True",
+ "batch_size": "auto",
+ "batch_sizes": [
+ 64
+ ],
+ "device": null,
+ "use_cache": null,
+ "limit": null,
+ "bootstrap_iters": 100000,
+ "gen_kwargs": null
+ },
+ "git_hash": "8281e96"
+}
\ No newline at end of file
diff --git a/lm-eval-output/rwkv-x-dev/r3-testchunk2/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/rwkv-x-dev/r3-testchunk2/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log
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