open-llm-leaderboard-old/details_unsloth__mistral-7b-v0.2

该数据集是在模型unsloth/mistral-7b-v0.2在Open LLM Leaderboard上进行评估运行期间自动创建的。它包含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，每次运行作为一个特定分割，使用运行的时间戳命名。train分割始终指向最新结果。额外的results配置存储了运行的所有聚合结果，用于在排行榜上计算和显示聚合指标。数据集为各种任务提供了详细的指标，包括准确度和标准误差。

原始信息汇总

数据集概述

数据集简介

该数据集是在对模型 unsloth/mistral-7b-v0.2 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集结构

• 配置数量：63个配置，每个配置对应一个评估任务。
• 运行次数：数据集由1次运行创建。每个运行在每个配置中作为一个特定的分割存在，分割名称使用运行的时间戳。
• 训练分割："train" 分割总是指向最新的结果。
• 结果配置：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。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_unsloth__mistral-7b-v0.2", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-24T15:13:21.174682 运行的最新结果：

python { "all": { "acc": 0.630812834707602, "acc_stderr": 0.03247743647091862, "acc_norm": 0.6370421584272593, "acc_norm_stderr": 0.03313961475675412, "mc1": 0.2778457772337821, "mc1_stderr": 0.015680929364024643, "mc2": 0.4179571372872378, "mc2_stderr": 0.014208894747074263 }, "harness|arc:challenge|25": { "acc": 0.568259385665529, "acc_stderr": 0.014474591427196202, "acc_norm": 0.6049488054607508, "acc_norm_stderr": 0.01428589829293817 }, "harness|hellaswag|10": { "acc": 0.6260705038836885, "acc_stderr": 0.00482856409062029, "acc_norm": 0.829416450906194, "acc_norm_stderr": 0.003753759220205047 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6074074074074074, "acc_stderr": 0.0421850621536888, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.0421850621536888 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6513157894736842, "acc_stderr": 0.0387813988879761, "acc_norm": 0.6513157894736842, "acc_norm_stderr": 0.0387813988879761 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.6, "acc_stderr": 0.04923659639173309, "acc_norm": 0.6, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6754716981132075, "acc_stderr": 0.028815615713432115, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.028815615713432115 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6944444444444444, "acc_stderr": 0.03852084696008534, "acc_norm": 0.6944444444444444, "acc_norm_stderr": 0.03852084696008534 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6358381502890174, "acc_stderr": 0.03669072477416906, "acc_norm": 0.6358381502890174, "acc_norm_stderr": 0.03669072477416906 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3137254901960784, "acc_stderr": 0.04617034827006716, "acc_norm": 0.3137254901960784, "acc_norm_stderr": 0.04617034827006716 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.0440844002276808, "acc_norm": 0.74, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5829787234042553, "acc_stderr": 0.03223276266711712, "acc_norm": 0.5829787234042553, "acc_norm_stderr": 0.03223276266711712 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.45614035087719296, "acc_stderr": 0.046854730419077895, "acc_norm": 0.45614035087719296, "acc_norm_stderr": 0.046854730419077895 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5724137931034483, "acc_stderr": 0.04122737111370332, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.04122737111370332 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3968253968253968, "acc_stderr": 0.025197101074246483, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.025197101074246483 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3888888888888889, "acc_stderr": 0.04360314860077459, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.04360314860077459 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7612903225806451, "acc_stderr": 0.02425107126220884, "acc_norm": 0.7612903225806451, "acc_norm_stderr": 0.02425107126220884 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5320197044334976, "acc_stderr": 0.035107665979592154, "acc_norm": 0.5320197044334976, "acc_norm_stderr": 0.035107665979592154 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.65, "acc_stderr": 0.04793724854411018, "acc_norm": 0.65, "acc_norm_stderr": 0.04793724854411018 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7636363636363637, "acc_stderr": 0.03317505930009181, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.03317505930009181 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7676767676767676, "acc_stderr": 0.03008862949021749, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.03008862949021749 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8756476683937824, "acc_stderr": 0.02381447708659355, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.02381447708659355 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6051282051282051, "acc_stderr": 0.024784316942156395, "acc_norm": 0.6051282051282051, "acc_norm_stderr": 0.024784316942156395 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3592592592592593, "acc_stderr": 0.029252905927251976, "acc_norm": 0.3592592592592593, "acc_norm_stderr": 0.029252905927251976