open-llm-leaderboard-old/details_Technoculture__MedMerge-6-7b-alpha-dpo

该数据集是在评估模型Technoculture/MedMerge-6-7b-alpha-dpo时自动创建的，主要用于在Open LLM Leaderboard上进行评估。数据集包含63个配置，每个配置对应一个评估任务。数据集由1次运行生成，每次运行的结果作为特定配置中的一个分割，分割名称使用运行的时间戳。train分割始终指向最新的结果。此外，results配置存储了所有运行的聚合结果，并用于计算和显示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型Technoculture/MedMerge-6-7b-alpha-dpo在Open LLM Leaderboard上的运行过程中自动创建的。

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。
• 额外的"results"配置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_Technoculture__MedMerge-6-7b-alpha-dpo", "harness_winogrande_5", split="train")

最新结果

以下是最新结果（注意可能包含其他任务的结果，每个任务的最新结果可以在"latest"分割中找到）：

python { "all": { "acc": 0.5256845888632714, "acc_stderr": 0.03422008390631278, "acc_norm": 0.530679668908867, "acc_norm_stderr": 0.034946938141584394, "mc1": 0.28518971848225216, "mc1_stderr": 0.015805827874454892, "mc2": 0.439400577032433, "mc2_stderr": 0.015027560307476687 }, "harness|arc:challenge|25": { "acc": 0.5119453924914675, "acc_stderr": 0.014607220340597171, "acc_norm": 0.5426621160409556, "acc_norm_stderr": 0.014558106543924067 }, "harness|hellaswag|10": { "acc": 0.5714997012547302, "acc_stderr": 0.004938500303990283, "acc_norm": 0.7560246962756423, "acc_norm_stderr": 0.004286002710084087 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5185185185185185, "acc_stderr": 0.043163785995113245, "acc_norm": 0.5185185185185185, "acc_norm_stderr": 0.043163785995113245 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.47368421052631576, "acc_stderr": 0.04063302731486671, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.04063302731486671 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6415094339622641, "acc_stderr": 0.02951470358398177, "acc_norm": 0.6415094339622641, "acc_norm_stderr": 0.02951470358398177 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5763888888888888, "acc_stderr": 0.041321250197233685, "acc_norm": 0.5763888888888888, "acc_norm_stderr": 0.041321250197233685 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4797687861271676, "acc_stderr": 0.03809342081273957, "acc_norm": 0.4797687861271676, "acc_norm_stderr": 0.03809342081273957 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.29411764705882354, "acc_stderr": 0.04533838195929776, "acc_norm": 0.29411764705882354, "acc_norm_stderr": 0.04533838195929776 }, "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": 0.4553191489361702, "acc_stderr": 0.03255525359340355, "acc_norm": 0.4553191489361702, "acc_norm_stderr": 0.03255525359340355 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.35964912280701755, "acc_stderr": 0.045144961328736334, "acc_norm": 0.35964912280701755, "acc_norm_stderr": 0.045144961328736334 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.46206896551724136, "acc_stderr": 0.04154659671707548, "acc_norm": 0.46206896551724136, "acc_norm_stderr": 0.04154659671707548 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3253968253968254, "acc_stderr": 0.02413015829976262, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.02413015829976262 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.29365079365079366, "acc_stderr": 0.04073524322147125, "acc_norm": 0.29365079365079366, "acc_norm_stderr": 0.04073524322147125 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.047609522856952365, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952365 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5741935483870968, "acc_stderr": 0.028129112709165904, "acc_norm": 0.5741935483870968, "acc_norm_stderr": 0.028129112709165904 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4482758620689655, "acc_stderr": 0.03499113137676744, "acc_norm": 0.4482758620689655, "acc_norm_stderr": 0.03499113137676744 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7212121212121212, "acc_stderr": 0.03501438706296781, "acc_norm": 0.7212121212121212, "acc_norm_stderr": 0.03501438706296781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6515151515151515, "acc_stderr": 0.033948539651564025, "acc_norm": 0.6515151515151515, "acc_norm_stderr": 0.033948539651564025 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7202072538860104, "acc_stderr": 0.032396370467357036, "acc_norm": 0.7202072538860104, "acc_norm_stderr": 0.032396370467357036 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.46923076923076923, "acc_stderr": 0.025302958890850154, "acc_norm": 0.46923076923076923, "acc_norm_stderr": 0.025302958890850154 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2740740740740741, "acc_stderr": 0.027195934804085622, "acc_norm": 0.27407407407407