open-llm-leaderboard/details_222limin__Liph-36-imatwarwithmyself

该数据集是在模型222limin/Liph-36-imatwarwithmyself在Open LLM Leaderboard上的评估运行期间自动创建的。它由63个配置组成，每个配置对应一个被评估的任务。数据集包含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，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。可以使用Hugging Face的datasets库加载该数据集，如提供的Python代码片段所示。

原始信息汇总

数据集概述

该数据集是在评估模型 222limin/Liph-36-imatwarwithmyself 在 Open LLM Leaderboard 上的自动创建的。

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。每个运行可以在每个配置中作为一个特定的分割找到，分割名称使用运行的 timestamp。
• "train" 分割总是指向最新的结果。
• 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_222limin__Liph-36-imatwarwithmyself", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-11T21:19:09.210629 运行的最新结果：

python { "all": { "acc": 0.5847932413836432, "acc_stderr": 0.0337639025326129, "acc_norm": 0.5853682529366641, "acc_norm_stderr": 0.034458499382190685, "mc1": 0.36964504283965727, "mc1_stderr": 0.01689818070697389, "mc2": 0.5227691702271635, "mc2_stderr": 0.015490392716934606 }, "harness|arc:challenge|25": { "acc": 0.5930034129692833, "acc_stderr": 0.014356399418009117, "acc_norm": 0.6237201365187713, "acc_norm_stderr": 0.014157022555407158 }, "harness|hellaswag|10": { "acc": 0.5860386377215694, "acc_stderr": 0.004915351107318752, "acc_norm": 0.7715594503087034, "acc_norm_stderr": 0.0041896988948855 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.045126085985421296, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421296 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5037037037037037, "acc_stderr": 0.04319223625811331, "acc_norm": 0.5037037037037037, "acc_norm_stderr": 0.04319223625811331 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5855263157894737, "acc_stderr": 0.04008973785779206, "acc_norm": 0.5855263157894737, "acc_norm_stderr": 0.04008973785779206 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5924528301886792, "acc_stderr": 0.030242233800854494, "acc_norm": 0.5924528301886792, "acc_norm_stderr": 0.030242233800854494 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6527777777777778, "acc_stderr": 0.039812405437178615, "acc_norm": 0.6527777777777778, "acc_norm_stderr": 0.039812405437178615 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.45, "acc_stderr": 0.04999999999999999, "acc_norm": 0.45, "acc_norm_stderr": 0.04999999999999999 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6011560693641619, "acc_stderr": 0.037336266553835096, "acc_norm": 0.6011560693641619, "acc_norm_stderr": 0.037336266553835096 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.39215686274509803, "acc_stderr": 0.04858083574266345, "acc_norm": 0.39215686274509803, "acc_norm_stderr": 0.04858083574266345 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.48936170212765956, "acc_stderr": 0.03267862331014063, "acc_norm": 0.48936170212765956, "acc_norm_stderr": 0.03267862331014063 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3684210526315789, "acc_stderr": 0.04537815354939391, "acc_norm": 0.3684210526315789, "acc_norm_stderr": 0.04537815354939391 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.496551724137931, "acc_stderr": 0.041665675771015785, "acc_norm": 0.496551724137931, "acc_norm_stderr": 0.041665675771015785 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.43386243386243384, "acc_stderr": 0.025525034382474894, "acc_norm": 0.43386243386243384, "acc_norm_stderr": 0.025525034382474894 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.40476190476190477, "acc_stderr": 0.04390259265377562, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.04390259265377562 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6935483870967742, "acc_stderr": 0.026226485652553883, "acc_norm": 0.6935483870967742, "acc_norm_stderr": 0.026226485652553883 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.45320197044334976, "acc_stderr": 0.03502544650845872, "acc_norm": 0.45320197044334976, "acc_norm_stderr": 0.03502544650845872 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7151515151515152, "acc_stderr": 0.035243908445117815, "acc_norm": 0.7151515151515152, "acc_norm_stderr": 0.035243908445117815 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7222222222222222, "acc_stderr": 0.03191178226713547, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.03191178226713547 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7927461139896373, "acc_stderr": 0.029252823291803624, "acc_norm": 0.7927461139896373, "acc_norm_stderr": 0.029252823291803624 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5923076923076923, "acc_stderr": 0.024915243985987847, "acc_norm": 0.5923076923076923, "acc_norm_stderr": 0.024915243985987847 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34074074074074073, "acc_stderr": 0.028897748741131137, "acc_norm": 0.34074074074074073, "acc_norm_stderr": 0.02889774