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README.md
CHANGED
@@ -3,8 +3,8 @@ pretty_name: Evaluation run of pszemraj/pythia-31m-goodwiki-deduped-2048-scratch
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dataset_summary: "Dataset automatically created during the evaluation run of model\
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\ [pszemraj/pythia-31m-goodwiki-deduped-2048-scratch](https://huggingface.co/pszemraj/pythia-31m-goodwiki-deduped-2048-scratch)\
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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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@@ -12,172 +12,19 @@ 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_pszemraj__pythia-31m-goodwiki-deduped-2048-scratch\"\
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,\n\t\"
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-
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\ that their might be results for other tasks in the repos if successive evals didn't\
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\ cover the same tasks. You find each in the results and the \"latest\" split for\
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\ each eval):\n\n```python\n{\n \"all\": {\n \"
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\ \"
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\ \"
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\ \"
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\ \"
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-
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\
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\ },\n \"harness|
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\ \"acc_stderr\": 0.
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-
\ \"acc_norm_stderr\": 0.004358764596401035\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
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-
: {\n \"acc\": 0.22,\n \"acc_stderr\": 0.04163331998932268,\n \
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\ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.04163331998932268\n \
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\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.18518518518518517,\n\
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\ \"acc_stderr\": 0.03355677216313142,\n \"acc_norm\": 0.18518518518518517,\n\
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\ \"acc_norm_stderr\": 0.03355677216313142\n },\n \"harness|hendrycksTest-astronomy|5\"\
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: {\n \"acc\": 0.17763157894736842,\n \"acc_stderr\": 0.031103182383123398,\n\
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\ \"acc_norm\": 0.17763157894736842,\n \"acc_norm_stderr\": 0.031103182383123398\n\
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\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.3,\n\
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\ \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\": 0.3,\n \
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\ \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
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: {\n \"acc\": 0.21509433962264152,\n \"acc_stderr\": 0.02528839450289137,\n\
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\ \"acc_norm\": 0.21509433962264152,\n \"acc_norm_stderr\": 0.02528839450289137\n\
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\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2569444444444444,\n\
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\ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.2569444444444444,\n\
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\ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
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-
: {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036845,\n \
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\ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036845\n },\n\
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-
\ \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\": 0.26,\n\
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-
\ \"acc_stderr\": 0.0440844002276808,\n \"acc_norm\": 0.26,\n \
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\ \"acc_norm_stderr\": 0.0440844002276808\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
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-
: {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \
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\ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \
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-
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.20809248554913296,\n\
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\ \"acc_stderr\": 0.030952890217749874,\n \"acc_norm\": 0.20809248554913296,\n\
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\ \"acc_norm_stderr\": 0.030952890217749874\n },\n \"harness|hendrycksTest-college_physics|5\"\
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: {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237654,\n\
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\ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237654\n\
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\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
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\ 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \"acc_norm\": 0.28,\n\
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\ \"acc_norm_stderr\": 0.045126085985421276\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
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-
: {\n \"acc\": 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102973,\n\
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\ \"acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102973\n\
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\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.23684210526315788,\n\
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\ \"acc_stderr\": 0.039994238792813365,\n \"acc_norm\": 0.23684210526315788,\n\
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\ \"acc_norm_stderr\": 0.039994238792813365\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
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: {\n \"acc\": 0.2413793103448276,\n \"acc_stderr\": 0.03565998174135302,\n\
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\ \"acc_norm\": 0.2413793103448276,\n \"acc_norm_stderr\": 0.03565998174135302\n\
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\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
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: 0.20899470899470898,\n \"acc_stderr\": 0.02094048156533486,\n \"\
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acc_norm\": 0.20899470899470898,\n \"acc_norm_stderr\": 0.02094048156533486\n\
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\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2857142857142857,\n\
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\ \"acc_stderr\": 0.04040610178208841,\n \"acc_norm\": 0.2857142857142857,\n\
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\ \"acc_norm_stderr\": 0.04040610178208841\n },\n \"harness|hendrycksTest-global_facts|5\"\
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: {\n \"acc\": 0.18,\n \"acc_stderr\": 0.038612291966536934,\n \
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\ \"acc_norm\": 0.18,\n \"acc_norm_stderr\": 0.038612291966536934\n \
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\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\
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: 0.1774193548387097,\n \"acc_stderr\": 0.02173254068932927,\n \"\
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acc_norm\": 0.1774193548387097,\n \"acc_norm_stderr\": 0.02173254068932927\n\
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\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
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: 0.15270935960591134,\n \"acc_stderr\": 0.02530890453938063,\n \"\
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acc_norm\": 0.15270935960591134,\n \"acc_norm_stderr\": 0.02530890453938063\n\
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\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
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\ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\
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: 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
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-
: {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\
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\ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\
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\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
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: 0.17676767676767677,\n \"acc_stderr\": 0.027178752639044915,\n \"\
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acc_norm\": 0.17676767676767677,\n \"acc_norm_stderr\": 0.027178752639044915\n\
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\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
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\ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860664,\n\
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\ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860664\n\
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\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
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\ \"acc\": 0.20256410256410257,\n \"acc_stderr\": 0.020377660970371372,\n\
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\ \"acc_norm\": 0.20256410256410257,\n \"acc_norm_stderr\": 0.020377660970371372\n\
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\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
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acc\": 0.2111111111111111,\n \"acc_stderr\": 0.024882116857655075,\n \
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\ \"acc_norm\": 0.2111111111111111,\n \"acc_norm_stderr\": 0.024882116857655075\n\
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\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
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\ \"acc\": 0.21008403361344538,\n \"acc_stderr\": 0.026461398717471874,\n\
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\ \"acc_norm\": 0.21008403361344538,\n \"acc_norm_stderr\": 0.026461398717471874\n\
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\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
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: 0.1986754966887417,\n \"acc_stderr\": 0.03257847384436776,\n \"\
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acc_norm\": 0.1986754966887417,\n \"acc_norm_stderr\": 0.03257847384436776\n\
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\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
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: 0.1926605504587156,\n \"acc_stderr\": 0.016909276884936094,\n \"\
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acc_norm\": 0.1926605504587156,\n \"acc_norm_stderr\": 0.016909276884936094\n\
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\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
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: 0.1527777777777778,\n \"acc_stderr\": 0.024536326026134224,\n \"\
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acc_norm\": 0.1527777777777778,\n \"acc_norm_stderr\": 0.024536326026134224\n\
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\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
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: 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\
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\ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\
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: {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\
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\ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\
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\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.31390134529147984,\n\
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\ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.31390134529147984,\n\
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\ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
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: {\n \"acc\": 0.2595419847328244,\n \"acc_stderr\": 0.03844876139785271,\n\
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\ \"acc_norm\": 0.2595419847328244,\n \"acc_norm_stderr\": 0.03844876139785271\n\
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\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
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\ 0.2396694214876033,\n \"acc_stderr\": 0.03896878985070417,\n \"\
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acc_norm\": 0.2396694214876033,\n \"acc_norm_stderr\": 0.03896878985070417\n\
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\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25925925925925924,\n\
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\ \"acc_stderr\": 0.042365112580946336,\n \"acc_norm\": 0.25925925925925924,\n\
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\ \"acc_norm_stderr\": 0.042365112580946336\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
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: {\n \"acc\": 0.22085889570552147,\n \"acc_stderr\": 0.032591773927421776,\n\
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\ \"acc_norm\": 0.22085889570552147,\n \"acc_norm_stderr\": 0.032591773927421776\n\
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\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\
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\ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\
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\ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\
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: {\n \"acc\": 0.17475728155339806,\n \"acc_stderr\": 0.037601780060266224,\n\
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\ \"acc_norm\": 0.17475728155339806,\n \"acc_norm_stderr\": 0.037601780060266224\n\
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\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2905982905982906,\n\
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\ \"acc_stderr\": 0.02974504857267404,\n \"acc_norm\": 0.2905982905982906,\n\
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\ \"acc_norm_stderr\": 0.02974504857267404\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
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: {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \
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\ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \
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\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.23627075351213284,\n\
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\ \"acc_stderr\": 0.015190473717037497,\n \"acc_norm\": 0.23627075351213284,\n\
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\ \"acc_norm_stderr\": 0.015190473717037497\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
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: {\n \"acc\": 0.24855491329479767,\n \"acc_stderr\": 0.023267528432100174,\n\
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\ \"acc_norm\": 0.24855491329479767,\n \"acc_norm_stderr\": 0.023267528432100174\n\
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\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23798882681564246,\n\
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\ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\
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\ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\
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: {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.023929155517351284,\n\
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\ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.023929155517351284\n\
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\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.1864951768488746,\n\
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\ \"acc_stderr\": 0.02212243977248077,\n \"acc_norm\": 0.1864951768488746,\n\
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\ \"acc_norm_stderr\": 0.02212243977248077\n },\n \"harness|hendrycksTest-prehistory|5\"\
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: {\n \"acc\": 0.21604938271604937,\n \"acc_stderr\": 0.022899162918445806,\n\
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\ \"acc_norm\": 0.21604938271604937,\n \"acc_norm_stderr\": 0.022899162918445806\n\
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\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
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acc\": 0.23404255319148937,\n \"acc_stderr\": 0.025257861359432417,\n \
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\ \"acc_norm\": 0.23404255319148937,\n \"acc_norm_stderr\": 0.025257861359432417\n\
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\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2457627118644068,\n\
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\ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\
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\ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
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: {\n \"acc\": 0.18382352941176472,\n \"acc_stderr\": 0.023529242185193106,\n\
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\ \"acc_norm\": 0.18382352941176472,\n \"acc_norm_stderr\": 0.023529242185193106\n\
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\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
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acc\": 0.25,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\
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: 0.25,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness|hendrycksTest-public_relations|5\"\
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-
: {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03955932861795833,\n\
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\ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03955932861795833\n\
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\ },\n \"harness|hendrycksTest-security_studies|5\": {\n \"acc\": 0.18775510204081633,\n\
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\ \"acc_stderr\": 0.02500025603954621,\n \"acc_norm\": 0.18775510204081633,\n\
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\ \"acc_norm_stderr\": 0.02500025603954621\n },\n \"harness|hendrycksTest-sociology|5\"\
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-
: {\n \"acc\": 0.24378109452736318,\n \"acc_stderr\": 0.03036049015401465,\n\
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\ \"acc_norm\": 0.24378109452736318,\n \"acc_norm_stderr\": 0.03036049015401465\n\
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\ },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\":\
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\ 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \"acc_norm\": 0.28,\n\
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\ \"acc_norm_stderr\": 0.04512608598542128\n },\n \"harness|hendrycksTest-virology|5\"\
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: {\n \"acc\": 0.28313253012048195,\n \"acc_stderr\": 0.03507295431370518,\n\
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\ \"acc_norm\": 0.28313253012048195,\n \"acc_norm_stderr\": 0.03507295431370518\n\
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\ },\n \"harness|hendrycksTest-world_religions|5\": {\n \"acc\": 0.3216374269005848,\n\
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\ \"acc_stderr\": 0.03582529442573122,\n \"acc_norm\": 0.3216374269005848,\n\
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\ \"acc_norm_stderr\": 0.03582529442573122\n },\n \"harness|truthfulqa:mc|0\"\
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-
: {\n \"mc1\": 0.24969400244798043,\n \"mc1_stderr\": 0.015152286907148128,\n\
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\ \"mc2\": 0.5131507278308213,\n \"mc2_stderr\": 0.01610246548451929\n\
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\ }\n}\n```"
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repo_url: https://huggingface.co/pszemraj/pythia-31m-goodwiki-deduped-2048-scratch
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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_2023-09-15T02-30-14.696113.parquet'
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- config_name: harness_hellaswag_10
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data_files:
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- split: 2023_09_15T02_30_14.696113
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@@ -782,14 +645,25 @@ configs:
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- split: latest
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path:
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- '**/details_harness|truthfulqa:mc|0_2023-09-15T02-30-14.696113.parquet'
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785 |
- config_name: results
|
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data_files:
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787 |
- split: 2023_09_15T02_30_14.696113
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788 |
path:
|
789 |
- results_2023-09-15T02-30-14.696113.parquet
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- split: latest
|
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path:
|
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-
- results_2023-
|
793 |
---
|
794 |
|
795 |
# Dataset Card for Evaluation run of pszemraj/pythia-31m-goodwiki-deduped-2048-scratch
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@@ -806,9 +680,9 @@ configs:
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|
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Dataset automatically created during the evaluation run of model [pszemraj/pythia-31m-goodwiki-deduped-2048-scratch](https://huggingface.co/pszemraj/pythia-31m-goodwiki-deduped-2048-scratch) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
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808 |
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-
The dataset is composed of
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-
The dataset has been created from
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812 |
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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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|
@@ -816,385 +690,37 @@ To load the details from a run, you can for instance do the following:
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816 |
```python
|
817 |
from datasets import load_dataset
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818 |
data = load_dataset("open-llm-leaderboard/details_pszemraj__pythia-31m-goodwiki-deduped-2048-scratch",
|
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-
"
|
820 |
split="train")
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```
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822 |
|
823 |
## Latest results
|
824 |
|
825 |
-
These are the [latest results from run 2023-
|
826 |
|
827 |
```python
|
828 |
{
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"all": {
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"
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"
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"
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"
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"
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"
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"
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850 |
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868 |
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|
1132 |
-
},
|
1133 |
-
"harness|hendrycksTest-professional_accounting|5": {
|
1134 |
-
"acc": 0.23404255319148937,
|
1135 |
-
"acc_stderr": 0.025257861359432417,
|
1136 |
-
"acc_norm": 0.23404255319148937,
|
1137 |
-
"acc_norm_stderr": 0.025257861359432417
|
1138 |
-
},
|
1139 |
-
"harness|hendrycksTest-professional_law|5": {
|
1140 |
-
"acc": 0.2457627118644068,
|
1141 |
-
"acc_stderr": 0.010996156635142692,
|
1142 |
-
"acc_norm": 0.2457627118644068,
|
1143 |
-
"acc_norm_stderr": 0.010996156635142692
|
1144 |
-
},
|
1145 |
-
"harness|hendrycksTest-professional_medicine|5": {
|
1146 |
-
"acc": 0.18382352941176472,
|
1147 |
-
"acc_stderr": 0.023529242185193106,
|
1148 |
-
"acc_norm": 0.18382352941176472,
|
1149 |
-
"acc_norm_stderr": 0.023529242185193106
|
1150 |
-
},
|
1151 |
-
"harness|hendrycksTest-professional_psychology|5": {
|
1152 |
-
"acc": 0.25,
|
1153 |
-
"acc_stderr": 0.01751781884501444,
|
1154 |
-
"acc_norm": 0.25,
|
1155 |
-
"acc_norm_stderr": 0.01751781884501444
|
1156 |
-
},
|
1157 |
-
"harness|hendrycksTest-public_relations|5": {
|
1158 |
-
"acc": 0.21818181818181817,
|
1159 |
-
"acc_stderr": 0.03955932861795833,
|
1160 |
-
"acc_norm": 0.21818181818181817,
|
1161 |
-
"acc_norm_stderr": 0.03955932861795833
|
1162 |
-
},
|
1163 |
-
"harness|hendrycksTest-security_studies|5": {
|
1164 |
-
"acc": 0.18775510204081633,
|
1165 |
-
"acc_stderr": 0.02500025603954621,
|
1166 |
-
"acc_norm": 0.18775510204081633,
|
1167 |
-
"acc_norm_stderr": 0.02500025603954621
|
1168 |
-
},
|
1169 |
-
"harness|hendrycksTest-sociology|5": {
|
1170 |
-
"acc": 0.24378109452736318,
|
1171 |
-
"acc_stderr": 0.03036049015401465,
|
1172 |
-
"acc_norm": 0.24378109452736318,
|
1173 |
-
"acc_norm_stderr": 0.03036049015401465
|
1174 |
-
},
|
1175 |
-
"harness|hendrycksTest-us_foreign_policy|5": {
|
1176 |
-
"acc": 0.28,
|
1177 |
-
"acc_stderr": 0.04512608598542128,
|
1178 |
-
"acc_norm": 0.28,
|
1179 |
-
"acc_norm_stderr": 0.04512608598542128
|
1180 |
-
},
|
1181 |
-
"harness|hendrycksTest-virology|5": {
|
1182 |
-
"acc": 0.28313253012048195,
|
1183 |
-
"acc_stderr": 0.03507295431370518,
|
1184 |
-
"acc_norm": 0.28313253012048195,
|
1185 |
-
"acc_norm_stderr": 0.03507295431370518
|
1186 |
-
},
|
1187 |
-
"harness|hendrycksTest-world_religions|5": {
|
1188 |
-
"acc": 0.3216374269005848,
|
1189 |
-
"acc_stderr": 0.03582529442573122,
|
1190 |
-
"acc_norm": 0.3216374269005848,
|
1191 |
-
"acc_norm_stderr": 0.03582529442573122
|
1192 |
-
},
|
1193 |
-
"harness|truthfulqa:mc|0": {
|
1194 |
-
"mc1": 0.24969400244798043,
|
1195 |
-
"mc1_stderr": 0.015152286907148128,
|
1196 |
-
"mc2": 0.5131507278308213,
|
1197 |
-
"mc2_stderr": 0.01610246548451929
|
1198 |
}
|
1199 |
}
|
1200 |
```
|
|
|
3 |
dataset_summary: "Dataset automatically created during the evaluation run of model\
|
4 |
\ [pszemraj/pythia-31m-goodwiki-deduped-2048-scratch](https://huggingface.co/pszemraj/pythia-31m-goodwiki-deduped-2048-scratch)\
|
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_pszemraj__pythia-31m-goodwiki-deduped-2048-scratch\"\
|
15 |
+
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
|
16 |
+
These are the [latest results from run 2023-10-29T03:01:00.285716](https://huggingface.co/datasets/open-llm-leaderboard/details_pszemraj__pythia-31m-goodwiki-deduped-2048-scratch/blob/main/results_2023-10-29T03-01-00.285716.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\": 0.00010486577181208053,\n\
|
20 |
+
\ \"em_stderr\": 0.00010486577181208337,\n \"f1\": 0.008596895973154373,\n\
|
21 |
+
\ \"f1_stderr\": 0.0005046567083861136,\n \"acc\": 0.2494080505130229,\n\
|
22 |
+
\ \"acc_stderr\": 0.007026223145264504\n },\n \"harness|drop|3\": {\n\
|
23 |
+
\ \"em\": 0.00010486577181208053,\n \"em_stderr\": 0.00010486577181208337,\n\
|
24 |
+
\ \"f1\": 0.008596895973154373,\n \"f1_stderr\": 0.0005046567083861136\n\
|
25 |
+
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\
|
26 |
+
: 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.4988161010260458,\n\
|
27 |
+
\ \"acc_stderr\": 0.014052446290529009\n }\n}\n```"
|
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|
28 |
repo_url: https://huggingface.co/pszemraj/pythia-31m-goodwiki-deduped-2048-scratch
|
29 |
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
|
30 |
point_of_contact: clementine@hf.co
|
|
|
37 |
- split: latest
|
38 |
path:
|
39 |
- '**/details_harness|arc:challenge|25_2023-09-15T02-30-14.696113.parquet'
|
40 |
+
- config_name: harness_drop_3
|
41 |
+
data_files:
|
42 |
+
- split: 2023_10_29T03_01_00.285716
|
43 |
+
path:
|
44 |
+
- '**/details_harness|drop|3_2023-10-29T03-01-00.285716.parquet'
|
45 |
+
- split: latest
|
46 |
+
path:
|
47 |
+
- '**/details_harness|drop|3_2023-10-29T03-01-00.285716.parquet'
|
48 |
+
- config_name: harness_gsm8k_5
|
49 |
+
data_files:
|
50 |
+
- split: 2023_10_29T03_01_00.285716
|
51 |
+
path:
|
52 |
+
- '**/details_harness|gsm8k|5_2023-10-29T03-01-00.285716.parquet'
|
53 |
+
- split: latest
|
54 |
+
path:
|
55 |
+
- '**/details_harness|gsm8k|5_2023-10-29T03-01-00.285716.parquet'
|
56 |
- config_name: harness_hellaswag_10
|
57 |
data_files:
|
58 |
- split: 2023_09_15T02_30_14.696113
|
|
|
645 |
- split: latest
|
646 |
path:
|
647 |
- '**/details_harness|truthfulqa:mc|0_2023-09-15T02-30-14.696113.parquet'
|
648 |
+
- config_name: harness_winogrande_5
|
649 |
+
data_files:
|
650 |
+
- split: 2023_10_29T03_01_00.285716
|
651 |
+
path:
|
652 |
+
- '**/details_harness|winogrande|5_2023-10-29T03-01-00.285716.parquet'
|
653 |
+
- split: latest
|
654 |
+
path:
|
655 |
+
- '**/details_harness|winogrande|5_2023-10-29T03-01-00.285716.parquet'
|
656 |
- config_name: results
|
657 |
data_files:
|
658 |
- split: 2023_09_15T02_30_14.696113
|
659 |
path:
|
660 |
- results_2023-09-15T02-30-14.696113.parquet
|
661 |
+
- split: 2023_10_29T03_01_00.285716
|
662 |
+
path:
|
663 |
+
- results_2023-10-29T03-01-00.285716.parquet
|
664 |
- split: latest
|
665 |
path:
|
666 |
+
- results_2023-10-29T03-01-00.285716.parquet
|
667 |
---
|
668 |
|
669 |
# Dataset Card for Evaluation run of pszemraj/pythia-31m-goodwiki-deduped-2048-scratch
|
|
|
680 |
|
681 |
Dataset automatically created during the evaluation run of model [pszemraj/pythia-31m-goodwiki-deduped-2048-scratch](https://huggingface.co/pszemraj/pythia-31m-goodwiki-deduped-2048-scratch) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
|
682 |
|
683 |
+
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
|
684 |
|
685 |
+
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.
|
686 |
|
687 |
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)).
|
688 |
|
|
|
690 |
```python
|
691 |
from datasets import load_dataset
|
692 |
data = load_dataset("open-llm-leaderboard/details_pszemraj__pythia-31m-goodwiki-deduped-2048-scratch",
|
693 |
+
"harness_winogrande_5",
|
694 |
split="train")
|
695 |
```
|
696 |
|
697 |
## Latest results
|
698 |
|
699 |
+
These are the [latest results from run 2023-10-29T03:01:00.285716](https://huggingface.co/datasets/open-llm-leaderboard/details_pszemraj__pythia-31m-goodwiki-deduped-2048-scratch/blob/main/results_2023-10-29T03-01-00.285716.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):
|
700 |
|
701 |
```python
|
702 |
{
|
703 |
"all": {
|
704 |
+
"em": 0.00010486577181208053,
|
705 |
+
"em_stderr": 0.00010486577181208337,
|
706 |
+
"f1": 0.008596895973154373,
|
707 |
+
"f1_stderr": 0.0005046567083861136,
|
708 |
+
"acc": 0.2494080505130229,
|
709 |
+
"acc_stderr": 0.007026223145264504
|
710 |
+
},
|
711 |
+
"harness|drop|3": {
|
712 |
+
"em": 0.00010486577181208053,
|
713 |
+
"em_stderr": 0.00010486577181208337,
|
714 |
+
"f1": 0.008596895973154373,
|
715 |
+
"f1_stderr": 0.0005046567083861136
|
716 |
+
},
|
717 |
+
"harness|gsm8k|5": {
|
718 |
+
"acc": 0.0,
|
719 |
+
"acc_stderr": 0.0
|
720 |
+
},
|
721 |
+
"harness|winogrande|5": {
|
722 |
+
"acc": 0.4988161010260458,
|
723 |
+
"acc_stderr": 0.014052446290529009
|
|
|
|
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|
724 |
}
|
725 |
}
|
726 |
```
|