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README.md
CHANGED
@@ -3,8 +3,8 @@ pretty_name: Evaluation run of Neko-Institute-of-Science/pygmalion-7b
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dataset_summary: "Dataset automatically created during the evaluation run of model\
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\ [Neko-Institute-of-Science/pygmalion-7b](https://huggingface.co/Neko-Institute-of-Science/pygmalion-7b)\
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\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
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\nThe dataset is composed of
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\ evaluated task.\n\nThe dataset has been created from
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\ found as a specific split in each configuration, the split being named using the\
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\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
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\nAn additional configuration \"results\" store all the aggregated results of the\
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@@ -12,173 +12,20 @@ dataset_summary: "Dataset automatically created during the evaluation run of mod
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\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
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\nTo load the details from a run, you can for instance do the following:\n```python\n\
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from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Neko-Institute-of-Science__pygmalion-7b\"\
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,\n\t\"
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\ },\n \"harness|
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\ \"
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\
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: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542129,\n \
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\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542129\n \
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\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4148148148148148,\n\
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\ \"acc_stderr\": 0.04256193767901408,\n \"acc_norm\": 0.4148148148148148,\n\
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\ \"acc_norm_stderr\": 0.04256193767901408\n },\n \"harness|hendrycksTest-astronomy|5\"\
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: {\n \"acc\": 0.3157894736842105,\n \"acc_stderr\": 0.03782728980865469,\n\
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\ \"acc_norm\": 0.3157894736842105,\n \"acc_norm_stderr\": 0.03782728980865469\n\
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\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.44,\n\
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\ \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.44,\n \
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\ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
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: {\n \"acc\": 0.39245283018867927,\n \"acc_stderr\": 0.030052580579557845,\n\
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\ \"acc_norm\": 0.39245283018867927,\n \"acc_norm_stderr\": 0.030052580579557845\n\
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\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.3680555555555556,\n\
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\ \"acc_stderr\": 0.04032999053960718,\n \"acc_norm\": 0.3680555555555556,\n\
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\ \"acc_norm_stderr\": 0.04032999053960718\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
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: {\n \"acc\": 0.27,\n \"acc_stderr\": 0.04461960433384741,\n \
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\ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.04461960433384741\n \
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\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
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: 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n\
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\ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
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: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \
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\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \
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\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.31213872832369943,\n\
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\ \"acc_stderr\": 0.035331333893236574,\n \"acc_norm\": 0.31213872832369943,\n\
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\ \"acc_norm_stderr\": 0.035331333893236574\n },\n \"harness|hendrycksTest-college_physics|5\"\
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: {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237655,\n\
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\ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237655\n\
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\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
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\ 0.44,\n \"acc_stderr\": 0.049888765156985884,\n \"acc_norm\": 0.44,\n\
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\ \"acc_norm_stderr\": 0.049888765156985884\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
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: {\n \"acc\": 0.37872340425531914,\n \"acc_stderr\": 0.03170995606040655,\n\
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\ \"acc_norm\": 0.37872340425531914,\n \"acc_norm_stderr\": 0.03170995606040655\n\
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\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2631578947368421,\n\
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\ \"acc_stderr\": 0.04142439719489362,\n \"acc_norm\": 0.2631578947368421,\n\
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\ \"acc_norm_stderr\": 0.04142439719489362\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
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: {\n \"acc\": 0.27586206896551724,\n \"acc_stderr\": 0.03724563619774632,\n\
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\ \"acc_norm\": 0.27586206896551724,\n \"acc_norm_stderr\": 0.03724563619774632\n\
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\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
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: 0.25132275132275134,\n \"acc_stderr\": 0.022340482339643898,\n \"\
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acc_norm\": 0.25132275132275134,\n \"acc_norm_stderr\": 0.022340482339643898\n\
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\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.24603174603174602,\n\
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\ \"acc_stderr\": 0.03852273364924316,\n \"acc_norm\": 0.24603174603174602,\n\
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\ \"acc_norm_stderr\": 0.03852273364924316\n },\n \"harness|hendrycksTest-global_facts|5\"\
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: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \
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\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \
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\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
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: 0.3580645161290323,\n \"acc_stderr\": 0.02727389059430064,\n \"\
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acc_norm\": 0.3580645161290323,\n \"acc_norm_stderr\": 0.02727389059430064\n\
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\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
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: 0.29064039408866993,\n \"acc_stderr\": 0.0319474007226554,\n \"\
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acc_norm\": 0.29064039408866993,\n \"acc_norm_stderr\": 0.0319474007226554\n\
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\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
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\ \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\
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: 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
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: {\n \"acc\": 0.4484848484848485,\n \"acc_stderr\": 0.03883565977956928,\n\
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\ \"acc_norm\": 0.4484848484848485,\n \"acc_norm_stderr\": 0.03883565977956928\n\
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\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
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: 0.3484848484848485,\n \"acc_stderr\": 0.033948539651564025,\n \"\
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acc_norm\": 0.3484848484848485,\n \"acc_norm_stderr\": 0.033948539651564025\n\
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\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
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\ \"acc\": 0.46113989637305697,\n \"acc_stderr\": 0.03597524411734578,\n\
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\ \"acc_norm\": 0.46113989637305697,\n \"acc_norm_stderr\": 0.03597524411734578\n\
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\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
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\ \"acc\": 0.36153846153846153,\n \"acc_stderr\": 0.024359581465396987,\n\
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\ \"acc_norm\": 0.36153846153846153,\n \"acc_norm_stderr\": 0.024359581465396987\n\
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\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
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acc\": 0.23703703703703705,\n \"acc_stderr\": 0.0259288761327661,\n \
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\ \"acc_norm\": 0.23703703703703705,\n \"acc_norm_stderr\": 0.0259288761327661\n\
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\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
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\ \"acc\": 0.3445378151260504,\n \"acc_stderr\": 0.03086868260412163,\n \
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\ \"acc_norm\": 0.3445378151260504,\n \"acc_norm_stderr\": 0.03086868260412163\n\
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\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
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: 0.2582781456953642,\n \"acc_stderr\": 0.035737053147634576,\n \"\
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acc_norm\": 0.2582781456953642,\n \"acc_norm_stderr\": 0.035737053147634576\n\
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\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
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: 0.47522935779816516,\n \"acc_stderr\": 0.02141099975363592,\n \"\
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acc_norm\": 0.47522935779816516,\n \"acc_norm_stderr\": 0.02141099975363592\n\
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\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
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: 0.28703703703703703,\n \"acc_stderr\": 0.030851992993257013,\n \"\
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acc_norm\": 0.28703703703703703,\n \"acc_norm_stderr\": 0.030851992993257013\n\
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\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
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: 0.4117647058823529,\n \"acc_stderr\": 0.0345423658538061,\n \"acc_norm\"\
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: 0.4117647058823529,\n \"acc_norm_stderr\": 0.0345423658538061\n },\n\
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\ \"harness|hendrycksTest-high_school_world_history|5\": {\n \"acc\":\
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\ 0.4219409282700422,\n \"acc_stderr\": 0.032148146302403695,\n \"\
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acc_norm\": 0.4219409282700422,\n \"acc_norm_stderr\": 0.032148146302403695\n\
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\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.3991031390134529,\n\
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\ \"acc_stderr\": 0.03286745312567961,\n \"acc_norm\": 0.3991031390134529,\n\
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\ \"acc_norm_stderr\": 0.03286745312567961\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
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: {\n \"acc\": 0.33587786259541985,\n \"acc_stderr\": 0.04142313771996664,\n\
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\ \"acc_norm\": 0.33587786259541985,\n \"acc_norm_stderr\": 0.04142313771996664\n\
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\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
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\ 0.5289256198347108,\n \"acc_stderr\": 0.04556710331269498,\n \"\
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acc_norm\": 0.5289256198347108,\n \"acc_norm_stderr\": 0.04556710331269498\n\
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\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.37037037037037035,\n\
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\ \"acc_stderr\": 0.04668408033024932,\n \"acc_norm\": 0.37037037037037035,\n\
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\ \"acc_norm_stderr\": 0.04668408033024932\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
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: {\n \"acc\": 0.37423312883435583,\n \"acc_stderr\": 0.03802068102899615,\n\
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\ \"acc_norm\": 0.37423312883435583,\n \"acc_norm_stderr\": 0.03802068102899615\n\
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\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.26785714285714285,\n\
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\ \"acc_stderr\": 0.04203277291467764,\n \"acc_norm\": 0.26785714285714285,\n\
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\ \"acc_norm_stderr\": 0.04203277291467764\n },\n \"harness|hendrycksTest-management|5\"\
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: {\n \"acc\": 0.3300970873786408,\n \"acc_stderr\": 0.046561471100123514,\n\
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\ \"acc_norm\": 0.3300970873786408,\n \"acc_norm_stderr\": 0.046561471100123514\n\
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\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.46153846153846156,\n\
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\ \"acc_stderr\": 0.03265903381186195,\n \"acc_norm\": 0.46153846153846156,\n\
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\ \"acc_norm_stderr\": 0.03265903381186195\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
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: {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \
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\ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \
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\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.4367816091954023,\n\
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\ \"acc_stderr\": 0.01773647083780068,\n \"acc_norm\": 0.4367816091954023,\n\
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\ \"acc_norm_stderr\": 0.01773647083780068\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
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: {\n \"acc\": 0.3959537572254335,\n \"acc_stderr\": 0.02632981334194625,\n\
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\ \"acc_norm\": 0.3959537572254335,\n \"acc_norm_stderr\": 0.02632981334194625\n\
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\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n\
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\ \"acc_stderr\": 0.014333522059217889,\n \"acc_norm\": 0.2424581005586592,\n\
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\ \"acc_norm_stderr\": 0.014333522059217889\n },\n \"harness|hendrycksTest-nutrition|5\"\
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: {\n \"acc\": 0.39869281045751637,\n \"acc_stderr\": 0.028036092273891765,\n\
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\ \"acc_norm\": 0.39869281045751637,\n \"acc_norm_stderr\": 0.028036092273891765\n\
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\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.38263665594855306,\n\
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\ \"acc_stderr\": 0.02760468902858198,\n \"acc_norm\": 0.38263665594855306,\n\
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\ \"acc_norm_stderr\": 0.02760468902858198\n },\n \"harness|hendrycksTest-prehistory|5\"\
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: {\n \"acc\": 0.35802469135802467,\n \"acc_stderr\": 0.026675611926037082,\n\
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\ \"acc_norm\": 0.35802469135802467,\n \"acc_norm_stderr\": 0.026675611926037082\n\
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\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
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acc\": 0.2624113475177305,\n \"acc_stderr\": 0.026244920349843007,\n \
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\ \"acc_norm\": 0.2624113475177305,\n \"acc_norm_stderr\": 0.026244920349843007\n\
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\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2985658409387223,\n\
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\ \"acc_stderr\": 0.011688060141794217,\n \"acc_norm\": 0.2985658409387223,\n\
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\ \"acc_norm_stderr\": 0.011688060141794217\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
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: {\n \"acc\": 0.44485294117647056,\n \"acc_stderr\": 0.03018753206032938,\n\
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\ \"acc_norm\": 0.44485294117647056,\n \"acc_norm_stderr\": 0.03018753206032938\n\
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\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
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acc\": 0.3562091503267974,\n \"acc_stderr\": 0.019373332420724493,\n \
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\ \"acc_norm\": 0.3562091503267974,\n \"acc_norm_stderr\": 0.019373332420724493\n\
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\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.4909090909090909,\n\
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\ \"acc_stderr\": 0.04788339768702861,\n \"acc_norm\": 0.4909090909090909,\n\
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\ \"acc_norm_stderr\": 0.04788339768702861\n },\n \"harness|hendrycksTest-security_studies|5\"\
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: {\n \"acc\": 0.3224489795918367,\n \"acc_stderr\": 0.029923100563683906,\n\
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\ \"acc_norm\": 0.3224489795918367,\n \"acc_norm_stderr\": 0.029923100563683906\n\
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\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.43283582089552236,\n\
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\ \"acc_stderr\": 0.0350349092367328,\n \"acc_norm\": 0.43283582089552236,\n\
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\ \"acc_norm_stderr\": 0.0350349092367328\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
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: {\n \"acc\": 0.43,\n \"acc_stderr\": 0.049756985195624284,\n \
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\ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n \
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\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.3493975903614458,\n\
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\ \"acc_stderr\": 0.0371172519074075,\n \"acc_norm\": 0.3493975903614458,\n\
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\ \"acc_norm_stderr\": 0.0371172519074075\n },\n \"harness|hendrycksTest-world_religions|5\"\
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: {\n \"acc\": 0.49122807017543857,\n \"acc_stderr\": 0.038342347441649924,\n\
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\ \"acc_norm\": 0.49122807017543857,\n \"acc_norm_stderr\": 0.038342347441649924\n\
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\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.23255813953488372,\n\
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\ \"mc1_stderr\": 0.014789157531080515,\n \"mc2\": 0.34541288814971643,\n\
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\ \"mc2_stderr\": 0.013437885426351232\n }\n}\n```"
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repo_url: https://huggingface.co/Neko-Institute-of-Science/pygmalion-7b
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leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
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point_of_contact: clementine@hf.co
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- split: latest
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path:
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- '**/details_harness|arc:challenge|25_2023-07-19T16:16:07.141450.parquet'
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- config_name: harness_hellaswag_10
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data_files:
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- split: 2023_07_19T16_16_07.141450
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- split: latest
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path:
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- '**/details_harness|truthfulqa:mc|0_2023-07-19T16:16:07.141450.parquet'
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- config_name: results
|
787 |
data_files:
|
788 |
- split: 2023_07_19T16_16_07.141450
|
789 |
path:
|
790 |
- results_2023-07-19T16:16:07.141450.parquet
|
|
|
|
|
|
|
791 |
- split: latest
|
792 |
path:
|
793 |
-
- results_2023-
|
794 |
---
|
795 |
|
796 |
# Dataset Card for Evaluation run of Neko-Institute-of-Science/pygmalion-7b
|
@@ -807,9 +681,9 @@ configs:
|
|
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|
808 |
Dataset automatically created during the evaluation run of model [Neko-Institute-of-Science/pygmalion-7b](https://huggingface.co/Neko-Institute-of-Science/pygmalion-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
|
809 |
|
810 |
-
The dataset is composed of
|
811 |
|
812 |
-
The dataset has been created from
|
813 |
|
814 |
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
|
815 |
|
@@ -817,385 +691,37 @@ To load the details from a run, you can for instance do the following:
|
|
817 |
```python
|
818 |
from datasets import load_dataset
|
819 |
data = load_dataset("open-llm-leaderboard/details_Neko-Institute-of-Science__pygmalion-7b",
|
820 |
-
"
|
821 |
split="train")
|
822 |
```
|
823 |
|
824 |
## Latest results
|
825 |
|
826 |
-
These are the [latest results from run 2023-
|
827 |
|
828 |
```python
|
829 |
{
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"
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"
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"
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"
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869 |
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"acc_stderr": 0.026244920349843007,
|
1137 |
-
"acc_norm": 0.2624113475177305,
|
1138 |
-
"acc_norm_stderr": 0.026244920349843007
|
1139 |
-
},
|
1140 |
-
"harness|hendrycksTest-professional_law|5": {
|
1141 |
-
"acc": 0.2985658409387223,
|
1142 |
-
"acc_stderr": 0.011688060141794217,
|
1143 |
-
"acc_norm": 0.2985658409387223,
|
1144 |
-
"acc_norm_stderr": 0.011688060141794217
|
1145 |
-
},
|
1146 |
-
"harness|hendrycksTest-professional_medicine|5": {
|
1147 |
-
"acc": 0.44485294117647056,
|
1148 |
-
"acc_stderr": 0.03018753206032938,
|
1149 |
-
"acc_norm": 0.44485294117647056,
|
1150 |
-
"acc_norm_stderr": 0.03018753206032938
|
1151 |
-
},
|
1152 |
-
"harness|hendrycksTest-professional_psychology|5": {
|
1153 |
-
"acc": 0.3562091503267974,
|
1154 |
-
"acc_stderr": 0.019373332420724493,
|
1155 |
-
"acc_norm": 0.3562091503267974,
|
1156 |
-
"acc_norm_stderr": 0.019373332420724493
|
1157 |
-
},
|
1158 |
-
"harness|hendrycksTest-public_relations|5": {
|
1159 |
-
"acc": 0.4909090909090909,
|
1160 |
-
"acc_stderr": 0.04788339768702861,
|
1161 |
-
"acc_norm": 0.4909090909090909,
|
1162 |
-
"acc_norm_stderr": 0.04788339768702861
|
1163 |
-
},
|
1164 |
-
"harness|hendrycksTest-security_studies|5": {
|
1165 |
-
"acc": 0.3224489795918367,
|
1166 |
-
"acc_stderr": 0.029923100563683906,
|
1167 |
-
"acc_norm": 0.3224489795918367,
|
1168 |
-
"acc_norm_stderr": 0.029923100563683906
|
1169 |
-
},
|
1170 |
-
"harness|hendrycksTest-sociology|5": {
|
1171 |
-
"acc": 0.43283582089552236,
|
1172 |
-
"acc_stderr": 0.0350349092367328,
|
1173 |
-
"acc_norm": 0.43283582089552236,
|
1174 |
-
"acc_norm_stderr": 0.0350349092367328
|
1175 |
-
},
|
1176 |
-
"harness|hendrycksTest-us_foreign_policy|5": {
|
1177 |
-
"acc": 0.43,
|
1178 |
-
"acc_stderr": 0.049756985195624284,
|
1179 |
-
"acc_norm": 0.43,
|
1180 |
-
"acc_norm_stderr": 0.049756985195624284
|
1181 |
-
},
|
1182 |
-
"harness|hendrycksTest-virology|5": {
|
1183 |
-
"acc": 0.3493975903614458,
|
1184 |
-
"acc_stderr": 0.0371172519074075,
|
1185 |
-
"acc_norm": 0.3493975903614458,
|
1186 |
-
"acc_norm_stderr": 0.0371172519074075
|
1187 |
-
},
|
1188 |
-
"harness|hendrycksTest-world_religions|5": {
|
1189 |
-
"acc": 0.49122807017543857,
|
1190 |
-
"acc_stderr": 0.038342347441649924,
|
1191 |
-
"acc_norm": 0.49122807017543857,
|
1192 |
-
"acc_norm_stderr": 0.038342347441649924
|
1193 |
-
},
|
1194 |
-
"harness|truthfulqa:mc|0": {
|
1195 |
-
"mc1": 0.23255813953488372,
|
1196 |
-
"mc1_stderr": 0.014789157531080515,
|
1197 |
-
"mc2": 0.34541288814971643,
|
1198 |
-
"mc2_stderr": 0.013437885426351232
|
1199 |
}
|
1200 |
}
|
1201 |
```
|
|
|
3 |
dataset_summary: "Dataset automatically created during the evaluation run of model\
|
4 |
\ [Neko-Institute-of-Science/pygmalion-7b](https://huggingface.co/Neko-Institute-of-Science/pygmalion-7b)\
|
5 |
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
|
6 |
+
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
|
7 |
+
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
|
8 |
\ found as a specific split in each configuration, the split being named using the\
|
9 |
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
|
10 |
\nAn additional configuration \"results\" store all the aggregated results of the\
|
|
|
12 |
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
|
13 |
\nTo load the details from a run, you can for instance do the following:\n```python\n\
|
14 |
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Neko-Institute-of-Science__pygmalion-7b\"\
|
15 |
+
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
|
16 |
+
These are the [latest results from run 2023-09-22T20:45:41.888775](https://huggingface.co/datasets/open-llm-leaderboard/details_Neko-Institute-of-Science__pygmalion-7b/blob/main/results_2023-09-22T20-45-41.888775.json)(note\
|
17 |
+
\ that their might be results for other tasks in the repos if successive evals didn't\
|
18 |
+
\ cover the same tasks. You find each in the results and the \"latest\" split for\
|
19 |
+
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0016778523489932886,\n\
|
20 |
+
\ \"em_stderr\": 0.00041913301788268467,\n \"f1\": 0.057855494966443086,\n\
|
21 |
+
\ \"f1_stderr\": 0.0013312169448543882,\n \"acc\": 0.3842127655245746,\n\
|
22 |
+
\ \"acc_stderr\": 0.009186954923281733\n },\n \"harness|drop|3\": {\n\
|
23 |
+
\ \"em\": 0.0016778523489932886,\n \"em_stderr\": 0.00041913301788268467,\n\
|
24 |
+
\ \"f1\": 0.057855494966443086,\n \"f1_stderr\": 0.0013312169448543882\n\
|
25 |
+
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.04624715693707354,\n \
|
26 |
+
\ \"acc_stderr\": 0.0057849916626918655\n },\n \"harness|winogrande|5\"\
|
27 |
+
: {\n \"acc\": 0.7221783741120757,\n \"acc_stderr\": 0.012588918183871601\n\
|
28 |
+
\ }\n}\n```"
|
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|
29 |
repo_url: https://huggingface.co/Neko-Institute-of-Science/pygmalion-7b
|
30 |
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
|
31 |
point_of_contact: clementine@hf.co
|
|
|
38 |
- split: latest
|
39 |
path:
|
40 |
- '**/details_harness|arc:challenge|25_2023-07-19T16:16:07.141450.parquet'
|
41 |
+
- config_name: harness_drop_3
|
42 |
+
data_files:
|
43 |
+
- split: 2023_09_22T20_45_41.888775
|
44 |
+
path:
|
45 |
+
- '**/details_harness|drop|3_2023-09-22T20-45-41.888775.parquet'
|
46 |
+
- split: latest
|
47 |
+
path:
|
48 |
+
- '**/details_harness|drop|3_2023-09-22T20-45-41.888775.parquet'
|
49 |
+
- config_name: harness_gsm8k_5
|
50 |
+
data_files:
|
51 |
+
- split: 2023_09_22T20_45_41.888775
|
52 |
+
path:
|
53 |
+
- '**/details_harness|gsm8k|5_2023-09-22T20-45-41.888775.parquet'
|
54 |
+
- split: latest
|
55 |
+
path:
|
56 |
+
- '**/details_harness|gsm8k|5_2023-09-22T20-45-41.888775.parquet'
|
57 |
- config_name: harness_hellaswag_10
|
58 |
data_files:
|
59 |
- split: 2023_07_19T16_16_07.141450
|
|
|
646 |
- split: latest
|
647 |
path:
|
648 |
- '**/details_harness|truthfulqa:mc|0_2023-07-19T16:16:07.141450.parquet'
|
649 |
+
- config_name: harness_winogrande_5
|
650 |
+
data_files:
|
651 |
+
- split: 2023_09_22T20_45_41.888775
|
652 |
+
path:
|
653 |
+
- '**/details_harness|winogrande|5_2023-09-22T20-45-41.888775.parquet'
|
654 |
+
- split: latest
|
655 |
+
path:
|
656 |
+
- '**/details_harness|winogrande|5_2023-09-22T20-45-41.888775.parquet'
|
657 |
- config_name: results
|
658 |
data_files:
|
659 |
- split: 2023_07_19T16_16_07.141450
|
660 |
path:
|
661 |
- results_2023-07-19T16:16:07.141450.parquet
|
662 |
+
- split: 2023_09_22T20_45_41.888775
|
663 |
+
path:
|
664 |
+
- results_2023-09-22T20-45-41.888775.parquet
|
665 |
- split: latest
|
666 |
path:
|
667 |
+
- results_2023-09-22T20-45-41.888775.parquet
|
668 |
---
|
669 |
|
670 |
# Dataset Card for Evaluation run of Neko-Institute-of-Science/pygmalion-7b
|
|
|
681 |
|
682 |
Dataset automatically created during the evaluation run of model [Neko-Institute-of-Science/pygmalion-7b](https://huggingface.co/Neko-Institute-of-Science/pygmalion-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
|
683 |
|
684 |
+
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
|
685 |
|
686 |
+
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
|
687 |
|
688 |
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
|
689 |
|
|
|
691 |
```python
|
692 |
from datasets import load_dataset
|
693 |
data = load_dataset("open-llm-leaderboard/details_Neko-Institute-of-Science__pygmalion-7b",
|
694 |
+
"harness_winogrande_5",
|
695 |
split="train")
|
696 |
```
|
697 |
|
698 |
## Latest results
|
699 |
|
700 |
+
These are the [latest results from run 2023-09-22T20:45:41.888775](https://huggingface.co/datasets/open-llm-leaderboard/details_Neko-Institute-of-Science__pygmalion-7b/blob/main/results_2023-09-22T20-45-41.888775.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
|
701 |
|
702 |
```python
|
703 |
{
|
704 |
"all": {
|
705 |
+
"em": 0.0016778523489932886,
|
706 |
+
"em_stderr": 0.00041913301788268467,
|
707 |
+
"f1": 0.057855494966443086,
|
708 |
+
"f1_stderr": 0.0013312169448543882,
|
709 |
+
"acc": 0.3842127655245746,
|
710 |
+
"acc_stderr": 0.009186954923281733
|
711 |
+
},
|
712 |
+
"harness|drop|3": {
|
713 |
+
"em": 0.0016778523489932886,
|
714 |
+
"em_stderr": 0.00041913301788268467,
|
715 |
+
"f1": 0.057855494966443086,
|
716 |
+
"f1_stderr": 0.0013312169448543882
|
717 |
+
},
|
718 |
+
"harness|gsm8k|5": {
|
719 |
+
"acc": 0.04624715693707354,
|
720 |
+
"acc_stderr": 0.0057849916626918655
|
721 |
+
},
|
722 |
+
"harness|winogrande|5": {
|
723 |
+
"acc": 0.7221783741120757,
|
724 |
+
"acc_stderr": 0.012588918183871601
|
|
|
|
|
|
|
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|
725 |
}
|
726 |
}
|
727 |
```
|