open-llm-leaderboard-old/details_mistralai__Mixtral-8x22B-Instruct-v0.1

该数据集是在模型mistralai/Mixtral-8x22B-Instruct-v0.1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。数据集是从1次运行中创建的，每次运行在每个配置中表示为特定的分割，分割名称使用运行的时间戳。train分割始终指向最新的结果。一个额外的配置results存储了运行的所有聚合结果，用于计算和显示Open LLM Leaderboard上的聚合指标。README还提供了如何使用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

数据集简介

该数据集是在对模型 mistralai/Mixtral-8x22B-Instruct-v0.1 进行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_mistralai__Mixtral-8x22B-Instruct-v0.1", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-18T04:27:50.095241 运行的最新结果：

python { "all": { "acc": 0.7770615259735991, "acc_stderr": 0.02783019667974498, "acc_norm": 0.7787918765106232, "acc_norm_stderr": 0.0283919646088637, "mc1": 0.5189718482252142, "mc1_stderr": 0.017490896405762357, "mc2": 0.6814472163688715, "mc2_stderr": 0.014593204740646692 }, "harness|arc:challenge|25": { "acc": 0.6860068259385665, "acc_stderr": 0.013562691224726291, "acc_norm": 0.726962457337884, "acc_norm_stderr": 0.013019332762635739 }, "harness|hellaswag|10": { "acc": 0.7118103963353913, "acc_stderr": 0.004519941716508372, "acc_norm": 0.8907588129854611, "acc_norm_stderr": 0.003113040606540135 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7481481481481481, "acc_stderr": 0.03749850709174022, "acc_norm": 0.7481481481481481, "acc_norm_stderr": 0.03749850709174022 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8618421052631579, "acc_stderr": 0.02808104293957655, "acc_norm": 0.8618421052631579, "acc_norm_stderr": 0.02808104293957655 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.77, "acc_stderr": 0.04229525846816506, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8226415094339623, "acc_stderr": 0.023508739218846938, "acc_norm": 0.8226415094339623, "acc_norm_stderr": 0.023508739218846938 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8958333333333334, "acc_stderr": 0.025545239210256917, "acc_norm": 0.8958333333333334, "acc_norm_stderr": 0.025545239210256917 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956911, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7630057803468208, "acc_stderr": 0.03242414757483098, "acc_norm": 0.7630057803468208, "acc_norm_stderr": 0.03242414757483098 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5784313725490197, "acc_stderr": 0.04913595201274504, "acc_norm": 0.5784313725490197, "acc_norm_stderr": 0.04913595201274504 }, "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": 0.7914893617021277, "acc_stderr": 0.026556982117838742, "acc_norm": 0.7914893617021277, "acc_norm_stderr": 0.026556982117838742 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.631578947368421, "acc_stderr": 0.04537815354939391, "acc_norm": 0.631578947368421, "acc_norm_stderr": 0.04537815354939391 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7586206896551724, "acc_stderr": 0.03565998174135302, "acc_norm": 0.7586206896551724, "acc_norm_stderr": 0.03565998174135302 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6243386243386243, "acc_stderr": 0.02494236893115978, "acc_norm": 0.6243386243386243, "acc_norm_stderr": 0.02494236893115978 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5952380952380952, "acc_stderr": 0.043902592653775635, "acc_norm": 0.5952380952380952, "acc_norm_stderr": 0.043902592653775635 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.9, "acc_stderr": 0.01706640371965726, "acc_norm": 0.9, "acc_norm_stderr": 0.01706640371965726 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6945812807881774, "acc_stderr": 0.03240661565868408, "acc_norm": 0.6945812807881774, "acc_norm_stderr": 0.03240661565868408 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.86, "acc_stderr": 0.03487350880197772, "acc_norm": 0.86, "acc_norm_stderr": 0.03487350880197772 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066573, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066573 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8939393939393939, "acc_stderr": 0.021938047738853106, "acc_norm": 0.8939393939393939, "acc_norm_stderr": 0.021938047738853106 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9689119170984456, "acc_stderr": 0.012525310625527029, "acc_norm": 0.9689119170984456, "acc_norm_stderr": 0.012525310625527029 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8128205128205128, "acc_stderr": 0.019776601086550043, "acc_norm": 0.8128205128205128, "acc_norm_stderr": 0.019776601086550043 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.5074074074074074, "acc_stderr": 0.0304821923951915, "acc_norm": 0.5074074074074074, "acc_norm_stderr": 0.0304821923951915 }, "harness|hendrycksTest-high_