open-llm-leaderboard-old/details_Chickaboo__ChickaQ

该数据集是在Open LLM Leaderboard上对模型Chickaboo/ChickaQ进行评估运行时自动创建的。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次运行中生成的，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。此外，还有一个results配置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。文件还提供了如何使用`datasets`库中的`load_dataset`函数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

该数据集是在评估模型 Chickaboo/ChickaQ 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

• 配置数量：63
• 数据来源：1 次运行（run）
• 数据分割：每个配置中包含特定运行的分割，分割名称使用运行的时间戳。"train" 分割始终指向最新结果。
• 额外配置："results" 配置存储所有运行的聚合结果，用于计算和显示聚合指标。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Chickaboo__ChickaQ", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-21T14:10:54.618600 运行 的最新结果：

python { "all": { "acc": 0.3659848060809438, "acc_stderr": 0.03373302007951669, "acc_norm": 0.37124839114399955, "acc_norm_stderr": 0.03461636251212984, "mc1": 0.22643818849449204, "mc1_stderr": 0.014651337324602588, "mc2": 0.47219104025186426, "mc2_stderr": 0.016351942852493542 }, "harness|arc:challenge|25": { "acc": 0.25341296928327645, "acc_stderr": 0.012710896778378606, "acc_norm": 0.29436860068259385, "acc_norm_stderr": 0.013318528460539426 }, "harness|hellaswag|10": { "acc": 0.3866759609639514, "acc_stderr": 0.004859930926500309, "acc_norm": 0.49153555068711413, "acc_norm_stderr": 0.004989066355449555 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.3851851851851852, "acc_stderr": 0.042039210401562783, "acc_norm": 0.3851851851851852, "acc_norm_stderr": 0.042039210401562783 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4407894736842105, "acc_stderr": 0.04040311062490436, "acc_norm": 0.4407894736842105, "acc_norm_stderr": 0.04040311062490436 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.36981132075471695, "acc_stderr": 0.02971142188010793, "acc_norm": 0.36981132075471695, "acc_norm_stderr": 0.02971142188010793 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3263888888888889, "acc_stderr": 0.03921067198982266, "acc_norm": 0.3263888888888889, "acc_norm_stderr": 0.03921067198982266 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.22, "acc_stderr": 0.041633319989322695, "acc_norm": 0.22, "acc_norm_stderr": 0.041633319989322695 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.27, "acc_stderr": 0.04461960433384741, "acc_norm": 0.27, "acc_norm_stderr": 0.04461960433384741 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.34104046242774566, "acc_stderr": 0.036146654241808254, "acc_norm": 0.34104046242774566, "acc_norm_stderr": 0.036146654241808254 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.22549019607843138, "acc_stderr": 0.041583075330832865, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.041583075330832865 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.2851063829787234, "acc_stderr": 0.02951319662553935, "acc_norm": 0.2851063829787234, "acc_norm_stderr": 0.02951319662553935 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.04266339443159394, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.04266339443159394 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4482758620689655, "acc_stderr": 0.04144311810878151, "acc_norm": 0.4482758620689655, "acc_norm_stderr": 0.04144311810878151 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2724867724867725, "acc_stderr": 0.022930973071633345, "acc_norm": 0.2724867724867725, "acc_norm_stderr": 0.022930973071633345 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.15873015873015872, "acc_stderr": 0.03268454013011743, "acc_norm": 0.15873015873015872, "acc_norm_stderr": 0.03268454013011743 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.3709677419354839, "acc_stderr": 0.02748054188795359, "acc_norm": 0.3709677419354839, "acc_norm_stderr": 0.02748054188795359 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33004926108374383, "acc_stderr": 0.03308530426228257, "acc_norm": 0.33004926108374383, "acc_norm_stderr": 0.03308530426228257 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.4666666666666667, "acc_stderr": 0.03895658065271846, "acc_norm": 0.4666666666666667, "acc_norm_stderr": 0.03895658065271846 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5202020202020202, "acc_stderr": 0.035594435655639176, "acc_norm": 0.5202020202020202, "acc_norm_stderr": 0.035594435655639176 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.47150259067357514, "acc_stderr": 0.036025735712884414, "acc_norm": 0.47150259067357514, "acc_norm_stderr": 0.036025735712884414 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.3, "acc_stderr": 0.023234581088428494, "acc_norm": 0.3, "acc_norm_stderr": 0.023234581088428494 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.26666666666666666, "acc_stderr": 0.026962424325073835, "acc_norm": 0.26666666666666666, "acc_norm_stderr": 0.026962424325073835 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc