Upload results for model google/gemma-7b-it
Browse files
data/google/gemma-7b-it/cot/24-04-09-07:34:14_idx20.json
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{
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"results": {
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"fuga-reprehenderit-4419_logiqa2_cot": {
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"acc,none": 0.2868956743002545,
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"acc_stderr,none": 0.011411702547829547,
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"alias": "fuga-reprehenderit-4419_logiqa2_cot"
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},
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"fuga-reprehenderit-4419_logiqa_cot": {
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"acc,none": 0.26677316293929715,
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"acc_stderr,none": 0.017690912581307214,
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"alias": "fuga-reprehenderit-4419_logiqa_cot"
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},
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"fuga-reprehenderit-4419_lsat-ar_cot": {
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"acc,none": 0.2,
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"acc_stderr,none": 0.026432744018203554,
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"alias": "fuga-reprehenderit-4419_lsat-ar_cot"
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},
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"fuga-reprehenderit-4419_lsat-lr_cot": {
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"acc,none": 0.23921568627450981,
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"acc_stderr,none": 0.018908919409402692,
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"alias": "fuga-reprehenderit-4419_lsat-lr_cot"
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},
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"fuga-reprehenderit-4419_lsat-rc_cot": {
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"acc,none": 0.26022304832713755,
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"acc_stderr,none": 0.02680130130545777,
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"alias": "fuga-reprehenderit-4419_lsat-rc_cot"
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}
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},
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"configs": {
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"fuga-reprehenderit-4419_logiqa2_cot": {
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"task": "fuga-reprehenderit-4419_logiqa2_cot",
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"group": "logikon-bench",
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"dataset_path": "cot-leaderboard/cot-eval-traces",
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"dataset_kwargs": {
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"data_files": {
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"test": "fuga-reprehenderit-4419-logiqa2/test-00000-of-00001.parquet"
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}
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},
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"test_split": "test",
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"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\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 += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "{{answer}}",
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"doc_to_choice": "{{options}}",
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"description": "",
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"target_delimiter": " ",
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+
"fewshot_delimiter": "\n\n",
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"num_fewshot": 0,
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+
"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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}
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},
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"fuga-reprehenderit-4419_logiqa_cot": {
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"task": "fuga-reprehenderit-4419_logiqa_cot",
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"group": "logikon-bench",
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"dataset_path": "cot-leaderboard/cot-eval-traces",
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"dataset_kwargs": {
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"data_files": {
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"test": "fuga-reprehenderit-4419-logiqa/test-00000-of-00001.parquet"
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}
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},
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"test_split": "test",
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"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\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 += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n",
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"doc_to_target": "{{answer}}",
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"doc_to_choice": "{{options}}",
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"description": "",
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+
"target_delimiter": " ",
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+
"fewshot_delimiter": "\n\n",
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"num_fewshot": 0,
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+
"metric_list": [
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{
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"metric": "acc",
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"aggregation": "mean",
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"higher_is_better": true
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}
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],
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"output_type": "multiple_choice",
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"repeats": 1,
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+
"should_decontaminate": false,
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"metadata": {
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"version": 0.0
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}
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},
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"fuga-reprehenderit-4419_lsat-ar_cot": {
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"task": "fuga-reprehenderit-4419_lsat-ar_cot",
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"group": "logikon-bench",
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"dataset_path": "cot-leaderboard/cot-eval-traces",
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"dataset_kwargs": {
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+
"data_files": {
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+
"test": "fuga-reprehenderit-4419-lsat-ar/test-00000-of-00001.parquet"
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+
}
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},
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"test_split": "test",
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+
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\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 += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n",
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+
"doc_to_target": "{{answer}}",
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+
"doc_to_choice": "{{options}}",
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+
"description": "",
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+
"target_delimiter": " ",
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+
"fewshot_delimiter": "\n\n",
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108 |
+
"num_fewshot": 0,
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109 |
+
"metric_list": [
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+
{
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+
"metric": "acc",
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+
"aggregation": "mean",
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113 |
+
"higher_is_better": true
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+
}
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+
],
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116 |
+
"output_type": "multiple_choice",
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117 |
+
"repeats": 1,
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118 |
+
"should_decontaminate": false,
|
119 |
+
"metadata": {
|
120 |
+
"version": 0.0
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121 |
+
}
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122 |
+
},
|
123 |
+
"fuga-reprehenderit-4419_lsat-lr_cot": {
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+
"task": "fuga-reprehenderit-4419_lsat-lr_cot",
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"group": "logikon-bench",
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126 |
+
"dataset_path": "cot-leaderboard/cot-eval-traces",
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+
"dataset_kwargs": {
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128 |
+
"data_files": {
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129 |
+
"test": "fuga-reprehenderit-4419-lsat-lr/test-00000-of-00001.parquet"
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+
}
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+
},
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+
"test_split": "test",
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+
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\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 += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n",
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+
"doc_to_target": "{{answer}}",
|
135 |
+
"doc_to_choice": "{{options}}",
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+
"description": "",
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137 |
+
"target_delimiter": " ",
|
138 |
+
"fewshot_delimiter": "\n\n",
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139 |
+
"num_fewshot": 0,
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140 |
+
"metric_list": [
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+
{
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142 |
+
"metric": "acc",
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143 |
+
"aggregation": "mean",
|
144 |
+
"higher_is_better": true
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145 |
+
}
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146 |
+
],
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147 |
+
"output_type": "multiple_choice",
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148 |
+
"repeats": 1,
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149 |
+
"should_decontaminate": false,
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150 |
+
"metadata": {
|
151 |
+
"version": 0.0
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152 |
+
}
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153 |
+
},
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154 |
+
"fuga-reprehenderit-4419_lsat-rc_cot": {
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155 |
+
"task": "fuga-reprehenderit-4419_lsat-rc_cot",
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156 |
+
"group": "logikon-bench",
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157 |
+
"dataset_path": "cot-leaderboard/cot-eval-traces",
|
158 |
+
"dataset_kwargs": {
|
159 |
+
"data_files": {
|
160 |
+
"test": "fuga-reprehenderit-4419-lsat-rc/test-00000-of-00001.parquet"
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161 |
+
}
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162 |
+
},
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163 |
+
"test_split": "test",
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164 |
+
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\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 += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n",
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165 |
+
"doc_to_target": "{{answer}}",
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166 |
+
"doc_to_choice": "{{options}}",
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167 |
+
"description": "",
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168 |
+
"target_delimiter": " ",
|
169 |
+
"fewshot_delimiter": "\n\n",
|
170 |
+
"num_fewshot": 0,
|
171 |
+
"metric_list": [
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172 |
+
{
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+
"metric": "acc",
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174 |
+
"aggregation": "mean",
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175 |
+
"higher_is_better": true
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176 |
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}
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177 |
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],
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178 |
+
"output_type": "multiple_choice",
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179 |
+
"repeats": 1,
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180 |
+
"should_decontaminate": false,
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181 |
+
"metadata": {
|
182 |
+
"version": 0.0
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183 |
+
}
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184 |
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}
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},
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"versions": {
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187 |
+
"fuga-reprehenderit-4419_logiqa2_cot": 0.0,
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188 |
+
"fuga-reprehenderit-4419_logiqa_cot": 0.0,
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189 |
+
"fuga-reprehenderit-4419_lsat-ar_cot": 0.0,
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190 |
+
"fuga-reprehenderit-4419_lsat-lr_cot": 0.0,
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191 |
+
"fuga-reprehenderit-4419_lsat-rc_cot": 0.0
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192 |
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},
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193 |
+
"n-shot": {
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194 |
+
"fuga-reprehenderit-4419_logiqa2_cot": 0,
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195 |
+
"fuga-reprehenderit-4419_logiqa_cot": 0,
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196 |
+
"fuga-reprehenderit-4419_lsat-ar_cot": 0,
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197 |
+
"fuga-reprehenderit-4419_lsat-lr_cot": 0,
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198 |
+
"fuga-reprehenderit-4419_lsat-rc_cot": 0
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199 |
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},
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200 |
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"config": {
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201 |
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"model": "vllm",
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202 |
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"model_args": "pretrained=google/gemma-7b-it,revision=main,dtype=bfloat16,tensor_parallel_size=2,gpu_memory_utilization=0.8,trust_remote_code=true,max_length=2048",
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203 |
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"batch_size": "auto",
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204 |
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"batch_sizes": [],
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205 |
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"device": null,
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206 |
+
"use_cache": null,
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207 |
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"limit": null,
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208 |
+
"bootstrap_iters": 100000,
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209 |
+
"gen_kwargs": null
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},
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211 |
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"git_hash": "741db1c"
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212 |
+
}
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