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README.md
CHANGED
@@ -3,8 +3,8 @@ pretty_name: Evaluation run of lmsys/vicuna-7b-v1.5-16k
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dataset_summary: "Dataset automatically created during the evaluation run of model\
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\ [lmsys/vicuna-7b-v1.5-16k](https://huggingface.co/lmsys/vicuna-7b-v1.5-16k) on\
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\ 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_lmsys__vicuna-7b-v1.5-16k\"\
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,\n\t\"
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\ \"
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\
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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\": 0.04512608598542128,\n \
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\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \
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\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4222222222222222,\n\
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\ \"acc_stderr\": 0.04266763404099582,\n \"acc_norm\": 0.4222222222222222,\n\
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\ \"acc_norm_stderr\": 0.04266763404099582\n },\n \"harness|hendrycksTest-astronomy|5\"\
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: {\n \"acc\": 0.4934210526315789,\n \"acc_stderr\": 0.040685900502249704,\n\
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\ \"acc_norm\": 0.4934210526315789,\n \"acc_norm_stderr\": 0.040685900502249704\n\
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\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.54,\n\
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\ \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.54,\n \
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\ \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
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: {\n \"acc\": 0.5132075471698113,\n \"acc_stderr\": 0.030762134874500476,\n\
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\ \"acc_norm\": 0.5132075471698113,\n \"acc_norm_stderr\": 0.030762134874500476\n\
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\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5,\n\
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\ \"acc_stderr\": 0.04181210050035455,\n \"acc_norm\": 0.5,\n \
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\ \"acc_norm_stderr\": 0.04181210050035455\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
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: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542127,\n \
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\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542127\n \
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\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
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: 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.42,\n\
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\ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
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: {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \
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\ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \
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\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4277456647398844,\n\
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\ \"acc_stderr\": 0.03772446857518027,\n \"acc_norm\": 0.4277456647398844,\n\
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\ \"acc_norm_stderr\": 0.03772446857518027\n },\n \"harness|hendrycksTest-college_physics|5\"\
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-
: {\n \"acc\": 0.2549019607843137,\n \"acc_stderr\": 0.043364327079931785,\n\
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\ \"acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.043364327079931785\n\
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\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
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\ 0.59,\n \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n\
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\ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
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: {\n \"acc\": 0.425531914893617,\n \"acc_stderr\": 0.03232146916224468,\n\
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\ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.03232146916224468\n\
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\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.40350877192982454,\n\
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\ \"acc_stderr\": 0.046151869625837026,\n \"acc_norm\": 0.40350877192982454,\n\
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\ \"acc_norm_stderr\": 0.046151869625837026\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
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: {\n \"acc\": 0.4827586206896552,\n \"acc_stderr\": 0.04164188720169377,\n\
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\ \"acc_norm\": 0.4827586206896552,\n \"acc_norm_stderr\": 0.04164188720169377\n\
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\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
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: 0.31746031746031744,\n \"acc_stderr\": 0.02397386199899206,\n \"\
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acc_norm\": 0.31746031746031744,\n \"acc_norm_stderr\": 0.02397386199899206\n\
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\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.30952380952380953,\n\
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\ \"acc_stderr\": 0.04134913018303316,\n \"acc_norm\": 0.30952380952380953,\n\
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\ \"acc_norm_stderr\": 0.04134913018303316\n },\n \"harness|hendrycksTest-global_facts|5\"\
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: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \
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\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \
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\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
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: 0.5483870967741935,\n \"acc_stderr\": 0.028310500348568392,\n \"\
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acc_norm\": 0.5483870967741935,\n \"acc_norm_stderr\": 0.028310500348568392\n\
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\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
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: 0.3399014778325123,\n \"acc_stderr\": 0.033327690684107895,\n \"\
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acc_norm\": 0.3399014778325123,\n \"acc_norm_stderr\": 0.033327690684107895\n\
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\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
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\ \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\"\
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: 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
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: {\n \"acc\": 0.6484848484848484,\n \"acc_stderr\": 0.0372820699868265,\n\
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\ \"acc_norm\": 0.6484848484848484,\n \"acc_norm_stderr\": 0.0372820699868265\n\
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\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
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: 0.6111111111111112,\n \"acc_stderr\": 0.0347327959083696,\n \"acc_norm\"\
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: 0.6111111111111112,\n \"acc_norm_stderr\": 0.0347327959083696\n },\n\
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\ \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \
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\ \"acc\": 0.694300518134715,\n \"acc_stderr\": 0.033248379397581594,\n\
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\ \"acc_norm\": 0.694300518134715,\n \"acc_norm_stderr\": 0.033248379397581594\n\
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\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
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\ \"acc\": 0.45384615384615384,\n \"acc_stderr\": 0.02524277098712618,\n\
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\ \"acc_norm\": 0.45384615384615384,\n \"acc_norm_stderr\": 0.02524277098712618\n\
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\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
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acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340496,\n \
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\ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340496\n\
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\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
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\ \"acc\": 0.4495798319327731,\n \"acc_stderr\": 0.03231293497137707,\n \
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\ \"acc_norm\": 0.4495798319327731,\n \"acc_norm_stderr\": 0.03231293497137707\n\
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\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
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: 0.2781456953642384,\n \"acc_stderr\": 0.03658603262763743,\n \"\
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acc_norm\": 0.2781456953642384,\n \"acc_norm_stderr\": 0.03658603262763743\n\
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\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
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: 0.6770642201834862,\n \"acc_stderr\": 0.020048115923415318,\n \"\
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acc_norm\": 0.6770642201834862,\n \"acc_norm_stderr\": 0.020048115923415318\n\
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\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
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: 0.3611111111111111,\n \"acc_stderr\": 0.03275773486100999,\n \"\
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acc_norm\": 0.3611111111111111,\n \"acc_norm_stderr\": 0.03275773486100999\n\
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\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
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: 0.6519607843137255,\n \"acc_stderr\": 0.03343311240488419,\n \"\
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acc_norm\": 0.6519607843137255,\n \"acc_norm_stderr\": 0.03343311240488419\n\
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\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
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acc\": 0.7130801687763713,\n \"acc_stderr\": 0.029443773022594693,\n \
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\ \"acc_norm\": 0.7130801687763713,\n \"acc_norm_stderr\": 0.029443773022594693\n\
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\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6188340807174888,\n\
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\ \"acc_stderr\": 0.03259625118416828,\n \"acc_norm\": 0.6188340807174888,\n\
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\ \"acc_norm_stderr\": 0.03259625118416828\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
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: {\n \"acc\": 0.5725190839694656,\n \"acc_stderr\": 0.04338920305792401,\n\
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\ \"acc_norm\": 0.5725190839694656,\n \"acc_norm_stderr\": 0.04338920305792401\n\
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\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
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\ 0.6033057851239669,\n \"acc_stderr\": 0.044658697805310094,\n \"\
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acc_norm\": 0.6033057851239669,\n \"acc_norm_stderr\": 0.044658697805310094\n\
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\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5555555555555556,\n\
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\ \"acc_stderr\": 0.04803752235190192,\n \"acc_norm\": 0.5555555555555556,\n\
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\ \"acc_norm_stderr\": 0.04803752235190192\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
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: {\n \"acc\": 0.5460122699386503,\n \"acc_stderr\": 0.0391170190467718,\n\
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\ \"acc_norm\": 0.5460122699386503,\n \"acc_norm_stderr\": 0.0391170190467718\n\
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\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.38392857142857145,\n\
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\ \"acc_stderr\": 0.04616143075028547,\n \"acc_norm\": 0.38392857142857145,\n\
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\ \"acc_norm_stderr\": 0.04616143075028547\n },\n \"harness|hendrycksTest-management|5\"\
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: {\n \"acc\": 0.6504854368932039,\n \"acc_stderr\": 0.047211885060971716,\n\
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\ \"acc_norm\": 0.6504854368932039,\n \"acc_norm_stderr\": 0.047211885060971716\n\
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\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7435897435897436,\n\
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\ \"acc_stderr\": 0.028605953702004243,\n \"acc_norm\": 0.7435897435897436,\n\
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\ \"acc_norm_stderr\": 0.028605953702004243\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
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: {\n \"acc\": 0.57,\n \"acc_stderr\": 0.049756985195624284,\n \
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\ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.049756985195624284\n \
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\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6551724137931034,\n\
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\ \"acc_stderr\": 0.016997123346113443,\n \"acc_norm\": 0.6551724137931034,\n\
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\ \"acc_norm_stderr\": 0.016997123346113443\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
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: {\n \"acc\": 0.5346820809248555,\n \"acc_stderr\": 0.02685425792825887,\n\
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\ \"acc_norm\": 0.5346820809248555,\n \"acc_norm_stderr\": 0.02685425792825887\n\
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\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24804469273743016,\n\
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\ \"acc_stderr\": 0.01444415780826144,\n \"acc_norm\": 0.24804469273743016,\n\
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\ \"acc_norm_stderr\": 0.01444415780826144\n },\n \"harness|hendrycksTest-nutrition|5\"\
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: {\n \"acc\": 0.5784313725490197,\n \"acc_stderr\": 0.028275490156791462,\n\
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\ \"acc_norm\": 0.5784313725490197,\n \"acc_norm_stderr\": 0.028275490156791462\n\
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\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5401929260450161,\n\
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\ \"acc_stderr\": 0.028306190403305696,\n \"acc_norm\": 0.5401929260450161,\n\
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\ \"acc_norm_stderr\": 0.028306190403305696\n },\n \"harness|hendrycksTest-prehistory|5\"\
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: {\n \"acc\": 0.5462962962962963,\n \"acc_stderr\": 0.0277012284685426,\n\
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\ \"acc_norm\": 0.5462962962962963,\n \"acc_norm_stderr\": 0.0277012284685426\n\
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\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
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acc\": 0.3971631205673759,\n \"acc_stderr\": 0.029189805673587105,\n \
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\ \"acc_norm\": 0.3971631205673759,\n \"acc_norm_stderr\": 0.029189805673587105\n\
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\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.35919165580182527,\n\
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\ \"acc_stderr\": 0.012253386187584253,\n \"acc_norm\": 0.35919165580182527,\n\
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\ \"acc_norm_stderr\": 0.012253386187584253\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
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: {\n \"acc\": 0.4852941176470588,\n \"acc_stderr\": 0.03035969707904611,\n\
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\ \"acc_norm\": 0.4852941176470588,\n \"acc_norm_stderr\": 0.03035969707904611\n\
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\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
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acc\": 0.48366013071895425,\n \"acc_stderr\": 0.020217030653186457,\n \
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\ \"acc_norm\": 0.48366013071895425,\n \"acc_norm_stderr\": 0.020217030653186457\n\
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\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6,\n\
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\ \"acc_stderr\": 0.0469237132203465,\n \"acc_norm\": 0.6,\n \
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\ \"acc_norm_stderr\": 0.0469237132203465\n },\n \"harness|hendrycksTest-security_studies|5\"\
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: {\n \"acc\": 0.5918367346938775,\n \"acc_stderr\": 0.03146465712827424,\n\
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\ \"acc_norm\": 0.5918367346938775,\n \"acc_norm_stderr\": 0.03146465712827424\n\
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\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6467661691542289,\n\
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\ \"acc_stderr\": 0.03379790611796777,\n \"acc_norm\": 0.6467661691542289,\n\
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\ \"acc_norm_stderr\": 0.03379790611796777\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
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: {\n \"acc\": 0.74,\n \"acc_stderr\": 0.04408440022768079,\n \
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\ \"acc_norm\": 0.74,\n \"acc_norm_stderr\": 0.04408440022768079\n \
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\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4397590361445783,\n\
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\ \"acc_stderr\": 0.03864139923699121,\n \"acc_norm\": 0.4397590361445783,\n\
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\ \"acc_norm_stderr\": 0.03864139923699121\n },\n \"harness|hendrycksTest-world_religions|5\"\
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: {\n \"acc\": 0.6783625730994152,\n \"acc_stderr\": 0.03582529442573122,\n\
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\ \"acc_norm\": 0.6783625730994152,\n \"acc_norm_stderr\": 0.03582529442573122\n\
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\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.33659730722154224,\n\
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\ \"mc1_stderr\": 0.016542412809494887,\n \"mc2\": 0.5041278188644791,\n\
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\ \"mc2_stderr\": 0.01576728095387478\n }\n}\n```"
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repo_url: https://huggingface.co/lmsys/vicuna-7b-v1.5-16k
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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_2023-08-18T07:58:23.659880.parquet'
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- config_name: harness_hellaswag_10
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data_files:
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- split: 2023_08_18T07_58_23.659880
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- split: latest
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path:
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- '**/details_harness|truthfulqa:mc|0_2023-08-18T07:58:23.659880.parquet'
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- config_name: results
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data_files:
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- split: 2023_08_18T07_58_23.659880
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path:
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- results_2023-08-18T07:58:23.659880.parquet
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- split: latest
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path:
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-
- results_2023-
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---
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# Dataset Card for Evaluation run of lmsys/vicuna-7b-v1.5-16k
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@@ -807,9 +681,9 @@ configs:
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Dataset automatically created during the evaluation run of model [lmsys/vicuna-7b-v1.5-16k](https://huggingface.co/lmsys/vicuna-7b-v1.5-16k) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
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The dataset is composed of
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The dataset has been created from
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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)).
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@@ -817,385 +691,37 @@ To load the details from a run, you can for instance do the following:
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```python
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from datasets import load_dataset
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data = load_dataset("open-llm-leaderboard/details_lmsys__vicuna-7b-v1.5-16k",
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"
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split="train")
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```
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## Latest results
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These are the [latest results from run 2023-
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```python
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{
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"all": {
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"acc": 0.35919165580182527,
|
1142 |
-
"acc_stderr": 0.012253386187584253,
|
1143 |
-
"acc_norm": 0.35919165580182527,
|
1144 |
-
"acc_norm_stderr": 0.012253386187584253
|
1145 |
-
},
|
1146 |
-
"harness|hendrycksTest-professional_medicine|5": {
|
1147 |
-
"acc": 0.4852941176470588,
|
1148 |
-
"acc_stderr": 0.03035969707904611,
|
1149 |
-
"acc_norm": 0.4852941176470588,
|
1150 |
-
"acc_norm_stderr": 0.03035969707904611
|
1151 |
-
},
|
1152 |
-
"harness|hendrycksTest-professional_psychology|5": {
|
1153 |
-
"acc": 0.48366013071895425,
|
1154 |
-
"acc_stderr": 0.020217030653186457,
|
1155 |
-
"acc_norm": 0.48366013071895425,
|
1156 |
-
"acc_norm_stderr": 0.020217030653186457
|
1157 |
-
},
|
1158 |
-
"harness|hendrycksTest-public_relations|5": {
|
1159 |
-
"acc": 0.6,
|
1160 |
-
"acc_stderr": 0.0469237132203465,
|
1161 |
-
"acc_norm": 0.6,
|
1162 |
-
"acc_norm_stderr": 0.0469237132203465
|
1163 |
-
},
|
1164 |
-
"harness|hendrycksTest-security_studies|5": {
|
1165 |
-
"acc": 0.5918367346938775,
|
1166 |
-
"acc_stderr": 0.03146465712827424,
|
1167 |
-
"acc_norm": 0.5918367346938775,
|
1168 |
-
"acc_norm_stderr": 0.03146465712827424
|
1169 |
-
},
|
1170 |
-
"harness|hendrycksTest-sociology|5": {
|
1171 |
-
"acc": 0.6467661691542289,
|
1172 |
-
"acc_stderr": 0.03379790611796777,
|
1173 |
-
"acc_norm": 0.6467661691542289,
|
1174 |
-
"acc_norm_stderr": 0.03379790611796777
|
1175 |
-
},
|
1176 |
-
"harness|hendrycksTest-us_foreign_policy|5": {
|
1177 |
-
"acc": 0.74,
|
1178 |
-
"acc_stderr": 0.04408440022768079,
|
1179 |
-
"acc_norm": 0.74,
|
1180 |
-
"acc_norm_stderr": 0.04408440022768079
|
1181 |
-
},
|
1182 |
-
"harness|hendrycksTest-virology|5": {
|
1183 |
-
"acc": 0.4397590361445783,
|
1184 |
-
"acc_stderr": 0.03864139923699121,
|
1185 |
-
"acc_norm": 0.4397590361445783,
|
1186 |
-
"acc_norm_stderr": 0.03864139923699121
|
1187 |
-
},
|
1188 |
-
"harness|hendrycksTest-world_religions|5": {
|
1189 |
-
"acc": 0.6783625730994152,
|
1190 |
-
"acc_stderr": 0.03582529442573122,
|
1191 |
-
"acc_norm": 0.6783625730994152,
|
1192 |
-
"acc_norm_stderr": 0.03582529442573122
|
1193 |
-
},
|
1194 |
-
"harness|truthfulqa:mc|0": {
|
1195 |
-
"mc1": 0.33659730722154224,
|
1196 |
-
"mc1_stderr": 0.016542412809494887,
|
1197 |
-
"mc2": 0.5041278188644791,
|
1198 |
-
"mc2_stderr": 0.01576728095387478
|
1199 |
}
|
1200 |
}
|
1201 |
```
|
|
|
3 |
dataset_summary: "Dataset automatically created during the evaluation run of model\
|
4 |
\ [lmsys/vicuna-7b-v1.5-16k](https://huggingface.co/lmsys/vicuna-7b-v1.5-16k) on\
|
5 |
\ 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_lmsys__vicuna-7b-v1.5-16k\"\
|
15 |
+
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
|
16 |
+
These are the [latest results from run 2023-10-19T11:48:14.833652](https://huggingface.co/datasets/open-llm-leaderboard/details_lmsys__vicuna-7b-v1.5-16k/blob/main/results_2023-10-19T11-48-14.833652.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\": 0.008389261744966443,\n\
|
20 |
+
\ \"em_stderr\": 0.0009340543216867012,\n \"f1\": 0.07163485738255039,\n\
|
21 |
+
\ \"f1_stderr\": 0.001675003372186539,\n \"acc\": 0.38778570501079185,\n\
|
22 |
+
\ \"acc_stderr\": 0.009750816499753356\n },\n \"harness|drop|3\": {\n\
|
23 |
+
\ \"em\": 0.008389261744966443,\n \"em_stderr\": 0.0009340543216867012,\n\
|
24 |
+
\ \"f1\": 0.07163485738255039,\n \"f1_stderr\": 0.001675003372186539\n\
|
25 |
+
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.06444275966641395,\n \
|
26 |
+
\ \"acc_stderr\": 0.006763391728488277\n },\n \"harness|winogrande|5\"\
|
27 |
+
: {\n \"acc\": 0.7111286503551697,\n \"acc_stderr\": 0.012738241271018436\n\
|
28 |
+
\ }\n}\n```"
|
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|
29 |
repo_url: https://huggingface.co/lmsys/vicuna-7b-v1.5-16k
|
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_2023-08-18T07:58:23.659880.parquet'
|
41 |
+
- config_name: harness_drop_3
|
42 |
+
data_files:
|
43 |
+
- split: 2023_10_19T11_48_14.833652
|
44 |
+
path:
|
45 |
+
- '**/details_harness|drop|3_2023-10-19T11-48-14.833652.parquet'
|
46 |
+
- split: latest
|
47 |
+
path:
|
48 |
+
- '**/details_harness|drop|3_2023-10-19T11-48-14.833652.parquet'
|
49 |
+
- config_name: harness_gsm8k_5
|
50 |
+
data_files:
|
51 |
+
- split: 2023_10_19T11_48_14.833652
|
52 |
+
path:
|
53 |
+
- '**/details_harness|gsm8k|5_2023-10-19T11-48-14.833652.parquet'
|
54 |
+
- split: latest
|
55 |
+
path:
|
56 |
+
- '**/details_harness|gsm8k|5_2023-10-19T11-48-14.833652.parquet'
|
57 |
- config_name: harness_hellaswag_10
|
58 |
data_files:
|
59 |
- split: 2023_08_18T07_58_23.659880
|
|
|
646 |
- split: latest
|
647 |
path:
|
648 |
- '**/details_harness|truthfulqa:mc|0_2023-08-18T07:58:23.659880.parquet'
|
649 |
+
- config_name: harness_winogrande_5
|
650 |
+
data_files:
|
651 |
+
- split: 2023_10_19T11_48_14.833652
|
652 |
+
path:
|
653 |
+
- '**/details_harness|winogrande|5_2023-10-19T11-48-14.833652.parquet'
|
654 |
+
- split: latest
|
655 |
+
path:
|
656 |
+
- '**/details_harness|winogrande|5_2023-10-19T11-48-14.833652.parquet'
|
657 |
- config_name: results
|
658 |
data_files:
|
659 |
- split: 2023_08_18T07_58_23.659880
|
660 |
path:
|
661 |
- results_2023-08-18T07:58:23.659880.parquet
|
662 |
+
- split: 2023_10_19T11_48_14.833652
|
663 |
+
path:
|
664 |
+
- results_2023-10-19T11-48-14.833652.parquet
|
665 |
- split: latest
|
666 |
path:
|
667 |
+
- results_2023-10-19T11-48-14.833652.parquet
|
668 |
---
|
669 |
|
670 |
# Dataset Card for Evaluation run of lmsys/vicuna-7b-v1.5-16k
|
|
|
681 |
|
682 |
Dataset automatically created during the evaluation run of model [lmsys/vicuna-7b-v1.5-16k](https://huggingface.co/lmsys/vicuna-7b-v1.5-16k) 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_lmsys__vicuna-7b-v1.5-16k",
|
694 |
+
"harness_winogrande_5",
|
695 |
split="train")
|
696 |
```
|
697 |
|
698 |
## Latest results
|
699 |
|
700 |
+
These are the [latest results from run 2023-10-19T11:48:14.833652](https://huggingface.co/datasets/open-llm-leaderboard/details_lmsys__vicuna-7b-v1.5-16k/blob/main/results_2023-10-19T11-48-14.833652.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": 0.008389261744966443,
|
706 |
+
"em_stderr": 0.0009340543216867012,
|
707 |
+
"f1": 0.07163485738255039,
|
708 |
+
"f1_stderr": 0.001675003372186539,
|
709 |
+
"acc": 0.38778570501079185,
|
710 |
+
"acc_stderr": 0.009750816499753356
|
711 |
+
},
|
712 |
+
"harness|drop|3": {
|
713 |
+
"em": 0.008389261744966443,
|
714 |
+
"em_stderr": 0.0009340543216867012,
|
715 |
+
"f1": 0.07163485738255039,
|
716 |
+
"f1_stderr": 0.001675003372186539
|
717 |
+
},
|
718 |
+
"harness|gsm8k|5": {
|
719 |
+
"acc": 0.06444275966641395,
|
720 |
+
"acc_stderr": 0.006763391728488277
|
721 |
+
},
|
722 |
+
"harness|winogrande|5": {
|
723 |
+
"acc": 0.7111286503551697,
|
724 |
+
"acc_stderr": 0.012738241271018436
|
|
|
|
|
|
|
|
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|
725 |
}
|
726 |
}
|
727 |
```
|