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open-llm-leaderboard-old/details_Changgil__K2S3-Mistral-7b-v1.3

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Hugging Face2024-04-02 更新2024-06-22 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_Changgil__K2S3-Mistral-7b-v1.3
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资源简介:
该数据集是在评估模型Changgil/K2S3-Mistral-7b-v1.3时自动创建的。数据集包含63个配置,每个配置对应一个评估任务。数据集由1次运行创建,每次运行的结果作为一个特定的分割,分割名称使用运行的时间戳。train分割始终指向最新的结果。此外,还有一个名为results的配置,存储了所有运行的聚合结果,用于计算和显示在Open LLM Leaderboard上的聚合指标。

该数据集是在评估模型Changgil/K2S3-Mistral-7b-v1.3时自动创建的。数据集包含63个配置,每个配置对应一个评估任务。数据集由1次运行创建,每次运行的结果作为一个特定的分割,分割名称使用运行的时间戳。train分割始终指向最新的结果。此外,还有一个名为results的配置,存储了所有运行的聚合结果,用于计算和显示在Open LLM Leaderboard上的聚合指标。
提供机构:
open-llm-leaderboard-old
原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型Changgil/K2S3-Mistral-7b-v1.3Open LLM Leaderboard上的自动创建的。

数据集组成

  • 数据集包含63个配置,每个配置对应一个评估任务。
  • 数据集从1次运行中创建,每个运行可以在每个配置中找到特定的分割,分割名称使用运行的时间戳。
  • "train"分割始终指向最新的结果。
  • 额外的配置"results"存储所有运行的聚合结果,用于计算和显示在Open LLM Leaderboard上的聚合指标。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Changgil__K2S3-Mistral-7b-v1.3", "harness_winogrande_5", split="train")

最新结果

以下是2024-04-02T18:29:16.852873运行的最新结果:

python { "all": { "acc": 0.5861724459991179, "acc_stderr": 0.033425967140901396, "acc_norm": 0.5878178399164371, "acc_norm_stderr": 0.03410952223944263, "mc1": 0.3182374541003672, "mc1_stderr": 0.01630598864892062, "mc2": 0.47207900025053434, "mc2_stderr": 0.014771984699656179 }, "harness|arc:challenge|25": { "acc": 0.5332764505119454, "acc_stderr": 0.014578995859605811, "acc_norm": 0.5810580204778157, "acc_norm_stderr": 0.01441810695363901 }, "harness|hellaswag|10": { "acc": 0.5932085241983669, "acc_stderr": 0.0049023140557256, "acc_norm": 0.7893845847440749, "acc_norm_stderr": 0.004069123905324908 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5407407407407407, "acc_stderr": 0.04304979692464241, "acc_norm": 0.5407407407407407, "acc_norm_stderr": 0.04304979692464241 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6447368421052632, "acc_stderr": 0.03894734487013317, "acc_norm": 0.6447368421052632, "acc_norm_stderr": 0.03894734487013317 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6150943396226415, "acc_stderr": 0.02994649856769995, "acc_norm": 0.6150943396226415, "acc_norm_stderr": 0.02994649856769995 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6875, "acc_stderr": 0.038760854559127644, "acc_norm": 0.6875, "acc_norm_stderr": 0.038760854559127644 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5549132947976878, "acc_stderr": 0.03789401760283648, "acc_norm": 0.5549132947976878, "acc_norm_stderr": 0.03789401760283648 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.30392156862745096, "acc_stderr": 0.04576665403207763, "acc_norm": 0.30392156862745096, "acc_norm_stderr": 0.04576665403207763 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4978723404255319, "acc_stderr": 0.032685726586674915, "acc_norm": 0.4978723404255319, "acc_norm_stderr": 0.032685726586674915 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3508771929824561, "acc_stderr": 0.044895393502707, "acc_norm": 0.3508771929824561, "acc_norm_stderr": 0.044895393502707 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482757, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482757 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41798941798941797, "acc_stderr": 0.025402555503260912, "acc_norm": 0.41798941798941797, "acc_norm_stderr": 0.025402555503260912 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04216370213557836, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04216370213557836 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7258064516129032, "acc_stderr": 0.025378139970885196, "acc_norm": 0.7258064516129032, "acc_norm_stderr": 0.025378139970885196 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4433497536945813, "acc_stderr": 0.03495334582162934, "acc_norm": 0.4433497536945813, "acc_norm_stderr": 0.03495334582162934 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7272727272727273, "acc_stderr": 0.0347769116216366, "acc_norm": 0.7272727272727273, "acc_norm_stderr": 0.0347769116216366 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7121212121212122, "acc_stderr": 0.03225883512300992, "acc_norm": 0.7121212121212122, "acc_norm_stderr": 0.03225883512300992 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8186528497409327, "acc_stderr": 0.02780703236068609, "acc_norm": 0.8186528497409327, "acc_norm_stderr": 0.02780703236068609 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5794871794871795, "acc_stderr": 0.02502861027671086, "acc_norm": 0.5794871794871795, "acc_norm_stderr": 0.02502861027671086 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3037037037037037, "acc_stderr": 0.028037929969114993, "acc_norm": 0.3037037037037037, "acc_norm_stderr": 0.028037929969114993 }, "

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