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README.md
CHANGED
@@ -3,8 +3,8 @@ pretty_name: Evaluation run of Sao10K/Stheno-1.3-L2-13B
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dataset_summary: "Dataset automatically created during the evaluation run of model\
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\ [Sao10K/Stheno-1.3-L2-13B](https://huggingface.co/Sao10K/Stheno-1.3-L2-13B) 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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@@ -12,172 +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_Sao10K__Stheno-1.3-L2-13B\"\
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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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\ },\n \"harness|
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\ \"
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\
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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-anatomy|5\": {\n \"acc\": 0.4666666666666667,\n\
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\ \"acc_stderr\": 0.043097329010363554,\n \"acc_norm\": 0.4666666666666667,\n\
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\ \"acc_norm_stderr\": 0.043097329010363554\n },\n \"harness|hendrycksTest-astronomy|5\"\
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: {\n \"acc\": 0.506578947368421,\n \"acc_stderr\": 0.040685900502249704,\n\
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\ \"acc_norm\": 0.506578947368421,\n \"acc_norm_stderr\": 0.040685900502249704\n\
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\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.53,\n\
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\ \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\": 0.53,\n \
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\ \"acc_norm_stderr\": 0.050161355804659205\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
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: {\n \"acc\": 0.5471698113207547,\n \"acc_stderr\": 0.030635627957961816,\n\
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\ \"acc_norm\": 0.5471698113207547,\n \"acc_norm_stderr\": 0.030635627957961816\n\
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\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5347222222222222,\n\
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\ \"acc_stderr\": 0.041711158581816184,\n \"acc_norm\": 0.5347222222222222,\n\
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\ \"acc_norm_stderr\": 0.041711158581816184\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
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: {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \
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\ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \
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\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
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: 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\": 0.44,\n\
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\ \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-college_mathematics|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-college_medicine|5\": {\n \"acc\": 0.4913294797687861,\n\
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\ \"acc_stderr\": 0.03811890988940412,\n \"acc_norm\": 0.4913294797687861,\n\
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\ \"acc_norm_stderr\": 0.03811890988940412\n },\n \"harness|hendrycksTest-college_physics|5\"\
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: {\n \"acc\": 0.3333333333333333,\n \"acc_stderr\": 0.04690650298201942,\n\
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\ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.04690650298201942\n\
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\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
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\ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\
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\ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
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: {\n \"acc\": 0.39148936170212767,\n \"acc_stderr\": 0.03190701242326812,\n\
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\ \"acc_norm\": 0.39148936170212767,\n \"acc_norm_stderr\": 0.03190701242326812\n\
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\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2982456140350877,\n\
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\ \"acc_stderr\": 0.04303684033537315,\n \"acc_norm\": 0.2982456140350877,\n\
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\ \"acc_norm_stderr\": 0.04303684033537315\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
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: {\n \"acc\": 0.503448275862069,\n \"acc_stderr\": 0.041665675771015785,\n\
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\ \"acc_norm\": 0.503448275862069,\n \"acc_norm_stderr\": 0.041665675771015785\n\
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\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
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: 0.2830687830687831,\n \"acc_stderr\": 0.02320139293819498,\n \"\
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acc_norm\": 0.2830687830687831,\n \"acc_norm_stderr\": 0.02320139293819498\n\
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\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.35714285714285715,\n\
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\ \"acc_stderr\": 0.042857142857142816,\n \"acc_norm\": 0.35714285714285715,\n\
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\ \"acc_norm_stderr\": 0.042857142857142816\n },\n \"harness|hendrycksTest-global_facts|5\"\
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: {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \
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\ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \
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\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.6161290322580645,\n\
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\ \"acc_stderr\": 0.027666182075539645,\n \"acc_norm\": 0.6161290322580645,\n\
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\ \"acc_norm_stderr\": 0.027666182075539645\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
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: {\n \"acc\": 0.4236453201970443,\n \"acc_stderr\": 0.03476725747649038,\n\
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\ \"acc_norm\": 0.4236453201970443,\n \"acc_norm_stderr\": 0.03476725747649038\n\
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\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
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\ \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\"\
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: 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
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: {\n \"acc\": 0.6424242424242425,\n \"acc_stderr\": 0.03742597043806587,\n\
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\ \"acc_norm\": 0.6424242424242425,\n \"acc_norm_stderr\": 0.03742597043806587\n\
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\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
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: 0.6818181818181818,\n \"acc_stderr\": 0.03318477333845331,\n \"\
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acc_norm\": 0.6818181818181818,\n \"acc_norm_stderr\": 0.03318477333845331\n\
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\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
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\ \"acc\": 0.7823834196891192,\n \"acc_stderr\": 0.029778663037752964,\n\
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\ \"acc_norm\": 0.7823834196891192,\n \"acc_norm_stderr\": 0.029778663037752964\n\
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\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
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\ \"acc\": 0.48205128205128206,\n \"acc_stderr\": 0.025334667080954932,\n\
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\ \"acc_norm\": 0.48205128205128206,\n \"acc_norm_stderr\": 0.025334667080954932\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\": 0.5168067226890757,\n \"acc_stderr\": 0.03246013680375308,\n \
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\ \"acc_norm\": 0.5168067226890757,\n \"acc_norm_stderr\": 0.03246013680375308\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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: 0.6954128440366972,\n \"acc_stderr\": 0.019732299420354045,\n \"\
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acc_norm\": 0.6954128440366972,\n \"acc_norm_stderr\": 0.019732299420354045\n\
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\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
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: 0.3333333333333333,\n \"acc_stderr\": 0.032149521478027514,\n \"\
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acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.032149521478027514\n\
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\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
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: 0.7450980392156863,\n \"acc_stderr\": 0.030587591351604257,\n \"\
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acc_norm\": 0.7450980392156863,\n \"acc_norm_stderr\": 0.030587591351604257\n\
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\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
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acc\": 0.6877637130801688,\n \"acc_stderr\": 0.03016513786784701,\n \
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\ \"acc_norm\": 0.6877637130801688,\n \"acc_norm_stderr\": 0.03016513786784701\n\
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\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6367713004484304,\n\
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\ \"acc_stderr\": 0.032277904428505,\n \"acc_norm\": 0.6367713004484304,\n\
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\ \"acc_norm_stderr\": 0.032277904428505\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
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: {\n \"acc\": 0.648854961832061,\n \"acc_stderr\": 0.04186445163013751,\n\
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\ \"acc_norm\": 0.648854961832061,\n \"acc_norm_stderr\": 0.04186445163013751\n\
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\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
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\ 0.7520661157024794,\n \"acc_stderr\": 0.03941897526516303,\n \"\
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acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.03941897526516303\n\
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\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.6851851851851852,\n\
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\ \"acc_stderr\": 0.04489931073591312,\n \"acc_norm\": 0.6851851851851852,\n\
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\ \"acc_norm_stderr\": 0.04489931073591312\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
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: {\n \"acc\": 0.6380368098159509,\n \"acc_stderr\": 0.037757007291414416,\n\
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\ \"acc_norm\": 0.6380368098159509,\n \"acc_norm_stderr\": 0.037757007291414416\n\
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\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.32142857142857145,\n\
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\ \"acc_stderr\": 0.04432804055291519,\n \"acc_norm\": 0.32142857142857145,\n\
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\ \"acc_norm_stderr\": 0.04432804055291519\n },\n \"harness|hendrycksTest-management|5\"\
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: {\n \"acc\": 0.6310679611650486,\n \"acc_stderr\": 0.0477761518115674,\n\
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\ \"acc_norm\": 0.6310679611650486,\n \"acc_norm_stderr\": 0.0477761518115674\n\
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\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7606837606837606,\n\
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\ \"acc_stderr\": 0.027951826808924336,\n \"acc_norm\": 0.7606837606837606,\n\
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\ \"acc_norm_stderr\": 0.027951826808924336\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
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: {\n \"acc\": 0.55,\n \"acc_stderr\": 0.049999999999999996,\n \
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\ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.049999999999999996\n \
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\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7113665389527458,\n\
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\ \"acc_stderr\": 0.016203792703197765,\n \"acc_norm\": 0.7113665389527458,\n\
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\ \"acc_norm_stderr\": 0.016203792703197765\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
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: {\n \"acc\": 0.5895953757225434,\n \"acc_stderr\": 0.026483392042098174,\n\
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\ \"acc_norm\": 0.5895953757225434,\n \"acc_norm_stderr\": 0.026483392042098174\n\
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\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2659217877094972,\n\
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\ \"acc_stderr\": 0.014776765066438888,\n \"acc_norm\": 0.2659217877094972,\n\
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\ \"acc_norm_stderr\": 0.014776765066438888\n },\n \"harness|hendrycksTest-nutrition|5\"\
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: {\n \"acc\": 0.5882352941176471,\n \"acc_stderr\": 0.02818059632825928,\n\
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\ \"acc_norm\": 0.5882352941176471,\n \"acc_norm_stderr\": 0.02818059632825928\n\
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\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6077170418006431,\n\
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\ \"acc_stderr\": 0.027731258647011994,\n \"acc_norm\": 0.6077170418006431,\n\
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\ \"acc_norm_stderr\": 0.027731258647011994\n },\n \"harness|hendrycksTest-prehistory|5\"\
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: {\n \"acc\": 0.6172839506172839,\n \"acc_stderr\": 0.027044538138402605,\n\
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\ \"acc_norm\": 0.6172839506172839,\n \"acc_norm_stderr\": 0.027044538138402605\n\
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\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
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acc\": 0.3829787234042553,\n \"acc_stderr\": 0.028999080904806185,\n \
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\ \"acc_norm\": 0.3829787234042553,\n \"acc_norm_stderr\": 0.028999080904806185\n\
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\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4041720990873533,\n\
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\ \"acc_stderr\": 0.012533504046491365,\n \"acc_norm\": 0.4041720990873533,\n\
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\ \"acc_norm_stderr\": 0.012533504046491365\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
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: {\n \"acc\": 0.5,\n \"acc_stderr\": 0.030372836961539352,\n \
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\ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.030372836961539352\n \
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\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"acc\"\
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: 0.5228758169934641,\n \"acc_stderr\": 0.02020665318788479,\n \"\
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acc_norm\": 0.5228758169934641,\n \"acc_norm_stderr\": 0.02020665318788479\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\": 0.6326530612244898,\n \"acc_stderr\": 0.03086214492108756,\n\
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\ \"acc_norm\": 0.6326530612244898,\n \"acc_norm_stderr\": 0.03086214492108756\n\
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\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7164179104477612,\n\
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\ \"acc_stderr\": 0.03187187537919797,\n \"acc_norm\": 0.7164179104477612,\n\
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\ \"acc_norm_stderr\": 0.03187187537919797\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
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: {\n \"acc\": 0.81,\n \"acc_stderr\": 0.039427724440366255,\n \
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\ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.039427724440366255\n \
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\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.463855421686747,\n\
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\ \"acc_stderr\": 0.03882310850890594,\n \"acc_norm\": 0.463855421686747,\n\
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\ \"acc_norm_stderr\": 0.03882310850890594\n },\n \"harness|hendrycksTest-world_religions|5\"\
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: {\n \"acc\": 0.7076023391812866,\n \"acc_stderr\": 0.03488647713457922,\n\
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\ \"acc_norm\": 0.7076023391812866,\n \"acc_norm_stderr\": 0.03488647713457922\n\
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\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.34761321909424725,\n\
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\ \"mc1_stderr\": 0.016670769188897303,\n \"mc2\": 0.5023124365778059,\n\
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\ \"mc2_stderr\": 0.015829473943426323\n }\n}\n```"
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repo_url: https://huggingface.co/Sao10K/Stheno-1.3-L2-13B
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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_2023-09-12T18-38-55.194574.parquet'
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- config_name: harness_hellaswag_10
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data_files:
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- split: 2023_09_12T18_38_55.194574
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- split: latest
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path:
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- '**/details_harness|truthfulqa:mc|0_2023-09-12T18-38-55.194574.parquet'
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- config_name: results
|
786 |
data_files:
|
787 |
- split: 2023_09_12T18_38_55.194574
|
788 |
path:
|
789 |
- results_2023-09-12T18-38-55.194574.parquet
|
|
|
|
|
|
|
790 |
- split: latest
|
791 |
path:
|
792 |
-
- results_2023-
|
793 |
---
|
794 |
|
795 |
# Dataset Card for Evaluation run of Sao10K/Stheno-1.3-L2-13B
|
@@ -806,9 +681,9 @@ configs:
|
|
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|
807 |
Dataset automatically created during the evaluation run of model [Sao10K/Stheno-1.3-L2-13B](https://huggingface.co/Sao10K/Stheno-1.3-L2-13B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
|
808 |
|
809 |
-
The dataset is composed of
|
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-
The dataset has been created from
|
812 |
|
813 |
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 +691,37 @@ To load the details from a run, you can for instance do the following:
|
|
816 |
```python
|
817 |
from datasets import load_dataset
|
818 |
data = load_dataset("open-llm-leaderboard/details_Sao10K__Stheno-1.3-L2-13B",
|
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-
"
|
820 |
split="train")
|
821 |
```
|
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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850 |
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1136 |
-
"acc_norm": 0.3829787234042553,
|
1137 |
-
"acc_norm_stderr": 0.028999080904806185
|
1138 |
-
},
|
1139 |
-
"harness|hendrycksTest-professional_law|5": {
|
1140 |
-
"acc": 0.4041720990873533,
|
1141 |
-
"acc_stderr": 0.012533504046491365,
|
1142 |
-
"acc_norm": 0.4041720990873533,
|
1143 |
-
"acc_norm_stderr": 0.012533504046491365
|
1144 |
-
},
|
1145 |
-
"harness|hendrycksTest-professional_medicine|5": {
|
1146 |
-
"acc": 0.5,
|
1147 |
-
"acc_stderr": 0.030372836961539352,
|
1148 |
-
"acc_norm": 0.5,
|
1149 |
-
"acc_norm_stderr": 0.030372836961539352
|
1150 |
-
},
|
1151 |
-
"harness|hendrycksTest-professional_psychology|5": {
|
1152 |
-
"acc": 0.5228758169934641,
|
1153 |
-
"acc_stderr": 0.02020665318788479,
|
1154 |
-
"acc_norm": 0.5228758169934641,
|
1155 |
-
"acc_norm_stderr": 0.02020665318788479
|
1156 |
-
},
|
1157 |
-
"harness|hendrycksTest-public_relations|5": {
|
1158 |
-
"acc": 0.6,
|
1159 |
-
"acc_stderr": 0.0469237132203465,
|
1160 |
-
"acc_norm": 0.6,
|
1161 |
-
"acc_norm_stderr": 0.0469237132203465
|
1162 |
-
},
|
1163 |
-
"harness|hendrycksTest-security_studies|5": {
|
1164 |
-
"acc": 0.6326530612244898,
|
1165 |
-
"acc_stderr": 0.03086214492108756,
|
1166 |
-
"acc_norm": 0.6326530612244898,
|
1167 |
-
"acc_norm_stderr": 0.03086214492108756
|
1168 |
-
},
|
1169 |
-
"harness|hendrycksTest-sociology|5": {
|
1170 |
-
"acc": 0.7164179104477612,
|
1171 |
-
"acc_stderr": 0.03187187537919797,
|
1172 |
-
"acc_norm": 0.7164179104477612,
|
1173 |
-
"acc_norm_stderr": 0.03187187537919797
|
1174 |
-
},
|
1175 |
-
"harness|hendrycksTest-us_foreign_policy|5": {
|
1176 |
-
"acc": 0.81,
|
1177 |
-
"acc_stderr": 0.039427724440366255,
|
1178 |
-
"acc_norm": 0.81,
|
1179 |
-
"acc_norm_stderr": 0.039427724440366255
|
1180 |
-
},
|
1181 |
-
"harness|hendrycksTest-virology|5": {
|
1182 |
-
"acc": 0.463855421686747,
|
1183 |
-
"acc_stderr": 0.03882310850890594,
|
1184 |
-
"acc_norm": 0.463855421686747,
|
1185 |
-
"acc_norm_stderr": 0.03882310850890594
|
1186 |
-
},
|
1187 |
-
"harness|hendrycksTest-world_religions|5": {
|
1188 |
-
"acc": 0.7076023391812866,
|
1189 |
-
"acc_stderr": 0.03488647713457922,
|
1190 |
-
"acc_norm": 0.7076023391812866,
|
1191 |
-
"acc_norm_stderr": 0.03488647713457922
|
1192 |
-
},
|
1193 |
-
"harness|truthfulqa:mc|0": {
|
1194 |
-
"mc1": 0.34761321909424725,
|
1195 |
-
"mc1_stderr": 0.016670769188897303,
|
1196 |
-
"mc2": 0.5023124365778059,
|
1197 |
-
"mc2_stderr": 0.015829473943426323
|
1198 |
}
|
1199 |
}
|
1200 |
```
|
|
|
3 |
dataset_summary: "Dataset automatically created during the evaluation run of model\
|
4 |
\ [Sao10K/Stheno-1.3-L2-13B](https://huggingface.co/Sao10K/Stheno-1.3-L2-13B) 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_Sao10K__Stheno-1.3-L2-13B\"\
|
15 |
+
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
|
16 |
+
These are the [latest results from run 2023-10-23T21:32:22.649999](https://huggingface.co/datasets/open-llm-leaderboard/details_Sao10K__Stheno-1.3-L2-13B/blob/main/results_2023-10-23T21-32-22.649999.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\": 0.2075293624161074,\n\
|
20 |
+
\ \"em_stderr\": 0.0041530868871623655,\n \"f1\": 0.3234186241610759,\n\
|
21 |
+
\ \"f1_stderr\": 0.004163889670714078,\n \"acc\": 0.35670155034816864,\n\
|
22 |
+
\ \"acc_stderr\": 0.00702519954294294\n },\n \"harness|drop|3\": {\n\
|
23 |
+
\ \"em\": 0.2075293624161074,\n \"em_stderr\": 0.0041530868871623655,\n\
|
24 |
+
\ \"f1\": 0.3234186241610759,\n \"f1_stderr\": 0.004163889670714078\n\
|
25 |
+
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.002274450341167551,\n \
|
26 |
+
\ \"acc_stderr\": 0.0013121578148674326\n },\n \"harness|winogrande|5\"\
|
27 |
+
: {\n \"acc\": 0.7111286503551697,\n \"acc_stderr\": 0.012738241271018446\n\
|
28 |
+
\ }\n}\n```"
|
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|
29 |
repo_url: https://huggingface.co/Sao10K/Stheno-1.3-L2-13B
|
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_2023-09-12T18-38-55.194574.parquet'
|
41 |
+
- config_name: harness_drop_3
|
42 |
+
data_files:
|
43 |
+
- split: 2023_10_23T21_32_22.649999
|
44 |
+
path:
|
45 |
+
- '**/details_harness|drop|3_2023-10-23T21-32-22.649999.parquet'
|
46 |
+
- split: latest
|
47 |
+
path:
|
48 |
+
- '**/details_harness|drop|3_2023-10-23T21-32-22.649999.parquet'
|
49 |
+
- config_name: harness_gsm8k_5
|
50 |
+
data_files:
|
51 |
+
- split: 2023_10_23T21_32_22.649999
|
52 |
+
path:
|
53 |
+
- '**/details_harness|gsm8k|5_2023-10-23T21-32-22.649999.parquet'
|
54 |
+
- split: latest
|
55 |
+
path:
|
56 |
+
- '**/details_harness|gsm8k|5_2023-10-23T21-32-22.649999.parquet'
|
57 |
- config_name: harness_hellaswag_10
|
58 |
data_files:
|
59 |
- split: 2023_09_12T18_38_55.194574
|
|
|
646 |
- split: latest
|
647 |
path:
|
648 |
- '**/details_harness|truthfulqa:mc|0_2023-09-12T18-38-55.194574.parquet'
|
649 |
+
- config_name: harness_winogrande_5
|
650 |
+
data_files:
|
651 |
+
- split: 2023_10_23T21_32_22.649999
|
652 |
+
path:
|
653 |
+
- '**/details_harness|winogrande|5_2023-10-23T21-32-22.649999.parquet'
|
654 |
+
- split: latest
|
655 |
+
path:
|
656 |
+
- '**/details_harness|winogrande|5_2023-10-23T21-32-22.649999.parquet'
|
657 |
- config_name: results
|
658 |
data_files:
|
659 |
- split: 2023_09_12T18_38_55.194574
|
660 |
path:
|
661 |
- results_2023-09-12T18-38-55.194574.parquet
|
662 |
+
- split: 2023_10_23T21_32_22.649999
|
663 |
+
path:
|
664 |
+
- results_2023-10-23T21-32-22.649999.parquet
|
665 |
- split: latest
|
666 |
path:
|
667 |
+
- results_2023-10-23T21-32-22.649999.parquet
|
668 |
---
|
669 |
|
670 |
# Dataset Card for Evaluation run of Sao10K/Stheno-1.3-L2-13B
|
|
|
681 |
|
682 |
Dataset automatically created during the evaluation run of model [Sao10K/Stheno-1.3-L2-13B](https://huggingface.co/Sao10K/Stheno-1.3-L2-13B) 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_Sao10K__Stheno-1.3-L2-13B",
|
694 |
+
"harness_winogrande_5",
|
695 |
split="train")
|
696 |
```
|
697 |
|
698 |
## Latest results
|
699 |
|
700 |
+
These are the [latest results from run 2023-10-23T21:32:22.649999](https://huggingface.co/datasets/open-llm-leaderboard/details_Sao10K__Stheno-1.3-L2-13B/blob/main/results_2023-10-23T21-32-22.649999.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": 0.2075293624161074,
|
706 |
+
"em_stderr": 0.0041530868871623655,
|
707 |
+
"f1": 0.3234186241610759,
|
708 |
+
"f1_stderr": 0.004163889670714078,
|
709 |
+
"acc": 0.35670155034816864,
|
710 |
+
"acc_stderr": 0.00702519954294294
|
711 |
+
},
|
712 |
+
"harness|drop|3": {
|
713 |
+
"em": 0.2075293624161074,
|
714 |
+
"em_stderr": 0.0041530868871623655,
|
715 |
+
"f1": 0.3234186241610759,
|
716 |
+
"f1_stderr": 0.004163889670714078
|
717 |
+
},
|
718 |
+
"harness|gsm8k|5": {
|
719 |
+
"acc": 0.002274450341167551,
|
720 |
+
"acc_stderr": 0.0013121578148674326
|
721 |
+
},
|
722 |
+
"harness|winogrande|5": {
|
723 |
+
"acc": 0.7111286503551697,
|
724 |
+
"acc_stderr": 0.012738241271018446
|
|
|
|
|
|
|
|
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|
725 |
}
|
726 |
}
|
727 |
```
|