open-llm-leaderboard-old/details_LeroyDyer__Mixtral_AI_base_128k

该数据集是在模型LeroyDyer/Mixtral_AI_base_128k在Open LLM Leaderboard上的评估运行期间自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。数据集包含一次运行的结果，每次运行在每个配置中表示为特定的分割。train分割始终指向最新的结果。一个名为results的额外配置存储了所有运行的聚合结果，这些结果用于计算和显示Open LLM Leaderboard上的聚合指标。README还提供了一个如何使用Python中的datasets库加载运行细节的示例。

原始信息汇总

数据集概述

数据集摘要

该数据集是在模型LeroyDyer/Mixtral_AI_base_128k的评估运行期间自动创建的，用于Open LLM Leaderboard。

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，每次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"results"配置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_LeroyDyer__Mixtral_AI_base_128k", "harness_winogrande_5", split="train")

最新结果

以下是最新结果（注意可能包含其他任务的结果，每个任务的最新结果可以在"results"和"latest"分割中找到）：

python { "all": { "acc": 0.6334020902872269, "acc_stderr": 0.032446084267638904, "acc_norm": 0.6373826158776669, "acc_norm_stderr": 0.03309582791924543, "mc1": 0.41615667074663404, "mc1_stderr": 0.017255657502903043, "mc2": 0.5810940106773435, "mc2_stderr": 0.015372089957769381 }, "harness|arc:challenge|25": { "acc": 0.6092150170648464, "acc_stderr": 0.01425856388051378, "acc_norm": 0.6510238907849829, "acc_norm_stderr": 0.013928933461382504 }, "harness|hellaswag|10": { "acc": 0.6555467038438558, "acc_stderr": 0.004742185169264768, "acc_norm": 0.8404700258912567, "acc_norm_stderr": 0.0036542123295166228 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.047609522856952365, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952365 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6, "acc_stderr": 0.04232073695151589, "acc_norm": 0.6, "acc_norm_stderr": 0.04232073695151589 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6710526315789473, "acc_stderr": 0.03823428969926604, "acc_norm": 0.6710526315789473, "acc_norm_stderr": 0.03823428969926604 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7094339622641509, "acc_stderr": 0.027943219989337135, "acc_norm": 0.7094339622641509, "acc_norm_stderr": 0.027943219989337135 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.75, "acc_stderr": 0.03621034121889507, "acc_norm": 0.75, "acc_norm_stderr": 0.03621034121889507 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "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": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6242774566473989, "acc_stderr": 0.03692820767264866, "acc_norm": 0.6242774566473989, "acc_norm_stderr": 0.03692820767264866 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4117647058823529, "acc_stderr": 0.048971049527263666, "acc_norm": 0.4117647058823529, "acc_norm_stderr": 0.048971049527263666 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.79, "acc_stderr": 0.04093601807403326, "acc_norm": 0.79, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5531914893617021, "acc_stderr": 0.0325005368436584, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.0325005368436584 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.04702880432049615, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.04702880432049615 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192118, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192118 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4021164021164021, "acc_stderr": 0.025253032554997695, "acc_norm": 0.4021164021164021, "acc_norm_stderr": 0.025253032554997695 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "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": 0.03510766597959215, "acc_norm": 0.5320197044334976, "acc_norm_stderr": 0.03510766597959215 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7454545454545455, "acc_stderr": 0.03401506715249039, "acc_norm": 0.7454545454545455, "acc_norm_stderr": 0.03401506715249039 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8181818181818182, "acc_stderr": 0.027479603010538808, "acc_norm": 0.8181818181818182, "acc_norm_stderr": 0.027479603010538808 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8601036269430051, "acc_stderr": 0.025033870583015178, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.025033870583015178 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6641025641025641, "acc_stderr": 0.023946724741563973, "acc_norm": 0.6641025641025641, "acc_norm_stderr": 0.023946724741563973 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34814814814814815, "acc_stderr": 0.029045600290616255, "acc_norm": 0.34814814814814815, "acc_norm_stderr": 0.029045600290616255 }, "harness|hendrycksTest-high_school_microeconomics|5": { "