open-llm-leaderboard-old/details_migtissera__Tess-2.0-Mixtral-v0.2
收藏数据集概述
数据集简介
该数据集是在评估模型 migtissera/Tess-2.0-Mixtral-v0.2 在 Open LLM Leaderboard 上的自动创建的。数据集包含 63 个配置，每个配置对应一个评估任务。
数据集结构
数据集由 1 次运行创建，每个运行可以在每个配置中找到特定的拆分，拆分名称使用运行的时间戳。"train" 拆分始终指向最新的结果。
额外配置
一个额外的配置 "results" 存储所有运行的聚合结果，用于计算和显示 Open LLM Leaderboard 上的聚合指标。
加载数据示例
python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_migtissera__Tess-2.0-Mixtral-v0.2", "harness_winogrande_5", split="train")
最新结果
这些是最新的结果，来自 2024-04-10T07:25:08.797488 的运行：
python { "all": { "acc": 0.7073511137871142, "acc_stderr": 0.030365163895926233, "acc_norm": 0.7114311022607525, "acc_norm_stderr": 0.030948684145173367, "mc1": 0.34761321909424725, "mc1_stderr": 0.016670769188897303, "mc2": 0.4892296257516054, "mc2_stderr": 0.014827343723490262 }, "harness|arc:challenge|25": { "acc": 0.6518771331058021, "acc_stderr": 0.01392100859517935, "acc_norm": 0.6800341296928327, "acc_norm_stderr": 0.013631345807016195 }, "harness|hellaswag|10": { "acc": 0.678550089623581, "acc_stderr": 0.004660785616933756, "acc_norm": 0.8666600278828919, "acc_norm_stderr": 0.003392470498816864 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.674074074074074, "acc_stderr": 0.040491220417025055, "acc_norm": 0.674074074074074, "acc_norm_stderr": 0.040491220417025055 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8157894736842105, "acc_stderr": 0.0315469804508223, "acc_norm": 0.8157894736842105, "acc_norm_stderr": 0.0315469804508223 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.71, "acc_stderr": 0.04560480215720684, "acc_norm": 0.71, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7811320754716982, "acc_stderr": 0.0254478638251086, "acc_norm": 0.7811320754716982, "acc_norm_stderr": 0.0254478638251086 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7916666666666666, "acc_stderr": 0.03396116205845334, "acc_norm": 0.7916666666666666, "acc_norm_stderr": 0.03396116205845334 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145633, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7109826589595376, "acc_stderr": 0.034564257450869974, "acc_norm": 0.7109826589595376, "acc_norm_stderr": 0.034564257450869974 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.43137254901960786, "acc_stderr": 0.04928099597287534, "acc_norm": 0.43137254901960786, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.039427724440366234, "acc_norm": 0.81, "acc_norm_stderr": 0.039427724440366234 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6978723404255319, "acc_stderr": 0.030017554471880557, "acc_norm": 0.6978723404255319, "acc_norm_stderr": 0.030017554471880557 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6578947368421053, "acc_stderr": 0.044629175353369376, "acc_norm": 0.6578947368421053, "acc_norm_stderr": 0.044629175353369376 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6620689655172414, "acc_stderr": 0.03941707632064891, "acc_norm": 0.6620689655172414, "acc_norm_stderr": 0.03941707632064891 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.48677248677248675, "acc_stderr": 0.025742297289575142, "acc_norm": 0.48677248677248675, "acc_norm_stderr": 0.025742297289575142 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5873015873015873, "acc_stderr": 0.04403438954768177, "acc_norm": 0.5873015873015873, "acc_norm_stderr": 0.04403438954768177 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8161290322580645, "acc_stderr": 0.02203721734026783, "acc_norm": 0.8161290322580645, "acc_norm_stderr": 0.02203721734026783 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6059113300492611, "acc_stderr": 0.034381579670365446, "acc_norm": 0.6059113300492611, "acc_norm_stderr": 0.034381579670365446 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7151515151515152, "acc_stderr": 0.03524390844511781, "acc_norm": 0.7151515151515152, "acc_norm_stderr": 0.03524390844511781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8535353535353535, "acc_stderr": 0.025190921114603918, "acc_norm": 0.8535353535353535, "acc_norm_stderr": 0.025190921114603918 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9430051813471503, "acc_stderr": 0.01673108529360755, "acc_norm": 0.9430051813471503, "acc_norm_stderr": 0.01673108529360755 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7128205128205128, "acc_stderr": 0.022939925418530616, "acc_norm": 0.7128205128205128, "acc_norm_stderr": 0.022939925418530616 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.362962962962963, "acc_stderr": 0.029318203645206865, "acc_norm": 0.362962962962963, "acc_norm_stderr": 0.029318203645206865 }, "harness|hendrycksTest-high_school_microeconomics|5": { "
