open-llm-leaderboard-old/details_Mihaiii__Cluj-Napoca-0.3

该数据集是在Open LLM Leaderboard上对模型Mihaiii/Cluj-Napoca-0.3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。它包含1次运行的结果，每次运行作为每个配置中的一个特定分割存储。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`函数加载数据集的示例。

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 Mihaiii/Cluj-Napoca-0.3 进行评估运行时自动创建的，评估结果展示在 Open LLM Leaderboard 上。

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。
• 数据集来自 1 次运行，每次运行在每个配置中都有一个特定的分割，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，用于计算和显示在 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_Mihaiii__Cluj-Napoca-0.3", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-24T23:20:22.784885 运行的最新结果：

python { "all": { "acc": 0.4635863169958793, "acc_stderr": 0.03410860206309599, "acc_norm": 0.47111138675230263, "acc_norm_stderr": 0.035040211592765776, "mc1": 0.30599755201958384, "mc1_stderr": 0.016132229728155045, "mc2": 0.47134573652723627, "mc2_stderr": 0.015936295762151154 }, "harness|arc:challenge|25": { "acc": 0.46245733788395904, "acc_stderr": 0.014570144495075576, "acc_norm": 0.492320819112628, "acc_norm_stderr": 0.014609667440892581 }, "harness|hellaswag|10": { "acc": 0.5141406094403506, "acc_stderr": 0.004987785530475672, "acc_norm": 0.7019518024297948, "acc_norm_stderr": 0.004564659775075923 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4, "acc_stderr": 0.04232073695151589, "acc_norm": 0.4, "acc_norm_stderr": 0.04232073695151589 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.42105263157894735, "acc_stderr": 0.040179012759817494, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.040179012759817494 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.42641509433962266, "acc_stderr": 0.03043779434298305, "acc_norm": 0.42641509433962266, "acc_norm_stderr": 0.03043779434298305 }, "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": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.24, "acc_stderr": 0.042923469599092816, "acc_norm": 0.24, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3815028901734104, "acc_stderr": 0.03703851193099521, "acc_norm": 0.3815028901734104, "acc_norm_stderr": 0.03703851193099521 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2647058823529412, "acc_stderr": 0.04389869956808778, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.04389869956808778 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.43829787234042555, "acc_stderr": 0.03243618636108101, "acc_norm": 0.43829787234042555, "acc_norm_stderr": 0.03243618636108101 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3157894736842105, "acc_stderr": 0.04372748290278008, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.04372748290278008 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.47586206896551725, "acc_stderr": 0.041618085035015295, "acc_norm": 0.47586206896551725, "acc_norm_stderr": 0.041618085035015295 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.36772486772486773, "acc_stderr": 0.02483383982556241, "acc_norm": 0.36772486772486773, "acc_norm_stderr": 0.02483383982556241 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.24603174603174602, "acc_stderr": 0.03852273364924318, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.03852273364924318 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.26, "acc_stderr": 0.044084400227680794, "acc_norm": 0.26, "acc_norm_stderr": 0.044084400227680794 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5258064516129032, "acc_stderr": 0.028406095057653315, "acc_norm": 0.5258064516129032, "acc_norm_stderr": 0.028406095057653315 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3054187192118227, "acc_stderr": 0.032406615658684086, "acc_norm": 0.3054187192118227, "acc_norm_stderr": 0.032406615658684086 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6121212121212121, "acc_stderr": 0.038049136539710114, "acc_norm": 0.6121212121212121, "acc_norm_stderr": 0.038049136539710114 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5505050505050505, "acc_stderr": 0.035441324919479704, "acc_norm": 0.5505050505050505, "acc_norm_stderr": 0.035441324919479704 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.689119170984456, "acc_stderr": 0.03340361906276588, "acc_norm": 0.689119170984456, "acc_norm_stderr": 0.03340361906276588 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4846153846153846, "acc_stderr": 0.02533900301010651, "acc_norm": 0.4846153846153846, "acc_norm_stderr": 0.02533900301010651 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.26666666666666666, "acc_stderr": 0.026962424325073817, "acc_norm": 0.26666666666666666, "acc_norm_stderr": 0.02