open-llm-leaderboard-old/details_Mihaiii__Pallas-0.5-LASER-0.6

该数据集是在Open LLM Leaderboard上对模型Mihaiii/Pallas-0.5-LASER-0.6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，每次运行在每个配置中表示为特定的分割。train分割始终指向最新结果。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`函数加载运行细节的示例。

原始信息汇总

数据集概述

该数据集是在对模型 Mihaiii/Pallas-0.5-LASER-0.6 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。每个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_Mihaiii__Pallas-0.5-LASER-0.6", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-05T05:07:56.399872 运行的最新结果：

python { "all": { "acc": 0.7349138515607955, "acc_stderr": 0.029135016661483534, "acc_norm": 0.7417675991344579, "acc_norm_stderr": 0.029675452495382785, "mc1": 0.39412484700122397, "mc1_stderr": 0.017106588140700325, "mc2": 0.5438686469941372, "mc2_stderr": 0.015945126478721837 }, "harness|arc:challenge|25": { "acc": 0.6109215017064846, "acc_stderr": 0.014247309976045609, "acc_norm": 0.6245733788395904, "acc_norm_stderr": 0.014150631435111726 }, "harness|hellaswag|10": { "acc": 0.6245767775343557, "acc_stderr": 0.00483242363059318, "acc_norm": 0.8159729137621987, "acc_norm_stderr": 0.003867143274914471 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7111111111111111, "acc_stderr": 0.03915450630414251, "acc_norm": 0.7111111111111111, "acc_norm_stderr": 0.03915450630414251 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8421052631578947, "acc_stderr": 0.02967416752010147, "acc_norm": 0.8421052631578947, "acc_norm_stderr": 0.02967416752010147 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7886792452830189, "acc_stderr": 0.025125766484827845, "acc_norm": 0.7886792452830189, "acc_norm_stderr": 0.025125766484827845 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8680555555555556, "acc_stderr": 0.02830096838204443, "acc_norm": 0.8680555555555556, "acc_norm_stderr": 0.02830096838204443 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7225433526011561, "acc_stderr": 0.03414014007044036, "acc_norm": 0.7225433526011561, "acc_norm_stderr": 0.03414014007044036 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5, "acc_stderr": 0.04975185951049946, "acc_norm": 0.5, "acc_norm_stderr": 0.04975185951049946 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036845, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7617021276595745, "acc_stderr": 0.027851252973889778, "acc_norm": 0.7617021276595745, "acc_norm_stderr": 0.027851252973889778 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5964912280701754, "acc_stderr": 0.04615186962583707, "acc_norm": 0.5964912280701754, "acc_norm_stderr": 0.04615186962583707 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7379310344827587, "acc_stderr": 0.03664666337225257, "acc_norm": 0.7379310344827587, "acc_norm_stderr": 0.03664666337225257 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6005291005291006, "acc_stderr": 0.02522545028406793, "acc_norm": 0.6005291005291006, "acc_norm_stderr": 0.02522545028406793 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5555555555555556, "acc_stderr": 0.04444444444444449, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.04444444444444449 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.9064516129032258, "acc_stderr": 0.01656575466827098, "acc_norm": 0.9064516129032258, "acc_norm_stderr": 0.01656575466827098 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6502463054187192, "acc_stderr": 0.03355400904969566, "acc_norm": 0.6502463054187192, "acc_norm_stderr": 0.03355400904969566 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.81, "acc_stderr": 0.039427724440366234, "acc_norm": 0.81, "acc_norm_stderr": 0.039427724440366234 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8303030303030303, "acc_stderr": 0.029311188674983116, "acc_norm": 0.8303030303030303, "acc_norm_stderr": 0.029311188674983116 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9090909090909091, "acc_stderr": 0.020482086775424225, "acc_norm": 0.9090909090909091, "acc_norm_stderr": 0.020482086775424225 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9740932642487047, "acc_stderr": 0.01146452335695318, "acc_norm": 0.9740932642487047, "acc_norm_stderr": 0.01146452335695318 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7871794871794872, "acc_stderr": 0.020752423722128013, "acc_norm": 0.7871794871794872, "acc_norm_stderr": 0.020752423722128013 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.4, "acc_stderr": 0.029869605095316897, "acc_norm": 0.4, "acc_norm_stderr": 0.029869605095316897 }, "harness|hendrycksTest-high_school_microeconomics|