open-llm-leaderboard-old/details_KnutJaegersberg__Deita-20b

该数据集是在Open LLM Leaderboard上对模型KnutJaegersberg/Deita-20b进行评估时自动创建的。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次运行中创建的，每次运行都可以在特定配置中找到，分割名使用运行的时间戳。train分割始终指向最新结果。此外，results配置存储了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。

原始信息汇总

数据集概述

该数据集是在评估模型 KnutJaegersberg/Deita-20b 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
• 创建来源：1 次运行
• 数据分割：每个配置包含特定分割，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" 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_KnutJaegersberg__Deita-20b", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-05T12:16:25.639871 运行 的最新结果：

python { "all": { "acc": 0.6757240714584833, "acc_stderr": 0.03164629743117511, "acc_norm": 0.6760877791494632, "acc_norm_stderr": 0.03231492887299232, "mc1": 0.41370869033047736, "mc1_stderr": 0.0172408618120998, "mc2": 0.572881968590399, "mc2_stderr": 0.015288640690271185 }, "harness|arc:challenge|25": { "acc": 0.6015358361774744, "acc_stderr": 0.014306946052735562, "acc_norm": 0.6390784982935154, "acc_norm_stderr": 0.014034761386175456 }, "harness|hellaswag|10": { "acc": 0.6315475004979088, "acc_stderr": 0.004813991069808273, "acc_norm": 0.8311093407687712, "acc_norm_stderr": 0.003738896244953813 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595853, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595853 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8092105263157895, "acc_stderr": 0.031975658210325, "acc_norm": 0.8092105263157895, "acc_norm_stderr": 0.031975658210325 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.71, "acc_stderr": 0.04560480215720683, "acc_norm": 0.71, "acc_norm_stderr": 0.04560480215720683 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7396226415094339, "acc_stderr": 0.027008766090708052, "acc_norm": 0.7396226415094339, "acc_norm_stderr": 0.027008766090708052 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8055555555555556, "acc_stderr": 0.03309615177059005, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.03309615177059005 }, "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": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6473988439306358, "acc_stderr": 0.036430371689585475, "acc_norm": 0.6473988439306358, "acc_norm_stderr": 0.036430371689585475 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.45098039215686275, "acc_stderr": 0.049512182523962625, "acc_norm": 0.45098039215686275, "acc_norm_stderr": 0.049512182523962625 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6595744680851063, "acc_stderr": 0.030976692998534432, "acc_norm": 0.6595744680851063, "acc_norm_stderr": 0.030976692998534432 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.047028804320496165, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.047028804320496165 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6206896551724138, "acc_stderr": 0.040434618619167466, "acc_norm": 0.6206896551724138, "acc_norm_stderr": 0.040434618619167466 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.5105820105820106, "acc_stderr": 0.02574554227604549, "acc_norm": 0.5105820105820106, "acc_norm_stderr": 0.02574554227604549 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5238095238095238, "acc_stderr": 0.04467062628403273, "acc_norm": 0.5238095238095238, "acc_norm_stderr": 0.04467062628403273 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8290322580645161, "acc_stderr": 0.02141724293632159, "acc_norm": 0.8290322580645161, "acc_norm_stderr": 0.02141724293632159 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5911330049261084, "acc_stderr": 0.034590588158832314, "acc_norm": 0.5911330049261084, "acc_norm_stderr": 0.034590588158832314 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.74, "acc_stderr": 0.044084400227680794, "acc_norm": 0.74, "acc_norm_stderr": 0.044084400227680794 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.793939393939394, "acc_stderr": 0.03158415324047712, "acc_norm": 0.793939393939394, "acc_norm_stderr": 0.03158415324047712 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8704663212435233, "acc_stderr": 0.024233532297758723, "acc_norm": 0.8704663212435233, "acc_norm_stderr": 0.024233532297758723 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6794871794871795, "acc_stderr": 0.02366129639396428, "acc_norm": 0.6794871794871795, "acc_norm_stderr": 0.02366129639396428 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3814814814814815, "acc_stderr": 0.0296167189274976, "acc_norm": 0.3814814814814815, "acc_norm_stderr": 0