open-llm-leaderboard-old/details_Rijgersberg__GEITje-7B-chat-v2

该数据集是在Open LLM Leaderboard上对模型Rijgersberg/GEITje-7B-chat-v2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次运行中生成的，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还提供了如何使用`datasets`库中的`load_dataset`函数加载运行中的详细信息的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 Rijgersberg/GEITje-7B-chat-v2 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

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。
• 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_Rijgersberg__GEITje-7B-chat-v2", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-19T15:31:36.828021 运行的最新结果：

python { "all": { "acc": 0.48880916708181743, "acc_stderr": 0.03442707322127932, "acc_norm": 0.4945295622293122, "acc_norm_stderr": 0.035197321298279766, "mc1": 0.2802937576499388, "mc1_stderr": 0.015723139524608767, "mc2": 0.4354583253052409, "mc2_stderr": 0.014644004519733833 }, "harness|arc:challenge|25": { "acc": 0.4658703071672355, "acc_stderr": 0.014577311315231102, "acc_norm": 0.5034129692832765, "acc_norm_stderr": 0.014611050403244081 }, "harness|hellaswag|10": { "acc": 0.5416251742680741, "acc_stderr": 0.004972460206842306, "acc_norm": 0.7412865962955587, "acc_norm_stderr": 0.00437032822483179 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.46710526315789475, "acc_stderr": 0.040601270352363966, "acc_norm": 0.46710526315789475, "acc_norm_stderr": 0.040601270352363966 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5207547169811321, "acc_stderr": 0.030746349975723463, "acc_norm": 0.5207547169811321, "acc_norm_stderr": 0.030746349975723463 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4722222222222222, "acc_stderr": 0.04174752578923185, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.04174752578923185 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4393063583815029, "acc_stderr": 0.037842719328874674, "acc_norm": 0.4393063583815029, "acc_norm_stderr": 0.037842719328874674 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237657, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237657 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3872340425531915, "acc_stderr": 0.03184389265339525, "acc_norm": 0.3872340425531915, "acc_norm_stderr": 0.03184389265339525 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.04266339443159393, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.04266339443159393 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.45517241379310347, "acc_stderr": 0.04149886942192117, "acc_norm": 0.45517241379310347, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.34656084656084657, "acc_stderr": 0.024508777521028424, "acc_norm": 0.34656084656084657, "acc_norm_stderr": 0.024508777521028424 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2777777777777778, "acc_stderr": 0.04006168083848878, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.04006168083848878 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.26, "acc_stderr": 0.04408440022768079, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5451612903225806, "acc_stderr": 0.028327743091561077, "acc_norm": 0.5451612903225806, "acc_norm_stderr": 0.028327743091561077 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.39408866995073893, "acc_stderr": 0.034381579670365446, "acc_norm": 0.39408866995073893, "acc_norm_stderr": 0.034381579670365446 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6666666666666666, "acc_stderr": 0.036810508691615514, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.036810508691615514 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6464646464646465, "acc_stderr": 0.03406086723547155, "acc_norm": 0.6464646464646465, "acc_norm_stderr": 0.03406086723547155 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6528497409326425, "acc_stderr": 0.03435696168361355, "acc_norm": 0.6528497409326425, "acc_norm_stderr": 0.03435696168361355 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.45384615384615384, "acc_stderr": 0.025242770987126188, "acc_norm": 0.45384615384615384, "acc_norm_stderr": 0.025242770987126188 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3037037037037037, "acc_stderr": 0.028037929969114993, "acc_norm": 0.3037037037