open-llm-leaderboard-old/details_gmonsoon__MiniCPM-2B-Base-v2

该数据集是在模型 gmonsoon/MiniCPM-2B-Base-v2 在 Open LLM Leaderboard 上的评估运行期间自动创建的。数据集由 63 个配置组成，每个配置对应一个被评估的任务。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 的额外配置存储了运行的所有聚合结果，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 Python 中的 datasets 库加载运行中的详细信息的示例。还包括了 2024-02-10 运行的最新结果，显示了不同任务的各种准确率指标。

原始信息汇总

数据集概述

数据集创建

• 来源: 该数据集是在评估模型 gmonsoon/MiniCPM-2B-Base-v2 在 Open LLM Leaderboard 上的自动创建的。

数据集结构

• 配置数量: 该数据集包含 63 个配置，每个配置对应一个评估任务。
• 创建次数: 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一个特定的分割，分割名称使用运行的时间戳。
• 训练分割: "train" 分割总是指向最新的结果。
• 结果配置: 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_gmonsoon__MiniCPM-2B-Base-v2", "harness_winogrande_5", split="train")

最新结果

• 最新结果来源: 这些是最新的结果，来自 2024-02-10T12:02:41.310734 的运行。
• 结果示例: python { "all": { "acc": 0.5253313411498812, "acc_stderr": 0.034432581057903915, "acc_norm": 0.5285384348837576, "acc_norm_stderr": 0.03513765074803403, "mc1": 0.26438188494492043, "mc1_stderr": 0.015438211119522512, "mc2": 0.40271915526124424, "mc2_stderr": 0.014482241680986031 }, "harness|arc:challenge|25": { "acc": 0.42662116040955633, "acc_stderr": 0.014453185592920293, "acc_norm": 0.4598976109215017, "acc_norm_stderr": 0.01456431885692485 }, "harness|hellaswag|10": { "acc": 0.5338577972515435, "acc_stderr": 0.004978328190775525, "acc_norm": 0.7221668990240988, "acc_norm_stderr": 0.0044701520816751265 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.42962962962962964, "acc_stderr": 0.04276349494376599, "acc_norm": 0.42962962962962964, "acc_norm_stderr": 0.04276349494376599 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5855263157894737, "acc_stderr": 0.04008973785779205, "acc_norm": 0.5855263157894737, "acc_norm_stderr": 0.04008973785779205 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.569811320754717, "acc_stderr": 0.030471445867183235, "acc_norm": 0.569811320754717, "acc_norm_stderr": 0.030471445867183235 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6180555555555556, "acc_stderr": 0.040629907841466674, "acc_norm": 0.6180555555555556, "acc_norm_stderr": 0.040629907841466674 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5317919075144508, "acc_stderr": 0.038047497443647646, "acc_norm": 0.5317919075144508, "acc_norm_stderr": 0.038047497443647646 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4117647058823529, "acc_stderr": 0.048971049527263666, "acc_norm": 0.4117647058823529, "acc_norm_stderr": 0.048971049527263666 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.39574468085106385, "acc_stderr": 0.031967586978353627, "acc_norm": 0.39574468085106385, "acc_norm_stderr": 0.031967586978353627 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3684210526315789, "acc_stderr": 0.04537815354939392, "acc_norm": 0.3684210526315789, "acc_norm_stderr": 0.04537815354939392 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.46206896551724136, "acc_stderr": 0.041546596717075474, "acc_norm": 0.46206896551724136, "acc_norm_stderr": 0.041546596717075474 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.36243386243386244, "acc_stderr": 0.024757473902752045, "acc_norm": 0.36243386243386244, "acc_norm_stderr": 0.024757473902752045 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3412698412698413, "acc_stderr": 0.04240799327574925, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.04240799327574925 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6548387096774193, "acc_stderr": 0.027045746573534327, "acc_norm": 0.6548387096774193, "acc_norm_stderr": 0.027045746573534327 }, "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": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5515151515151515, "acc_stderr": 0.03883565977956929, "acc_norm": 0.5515151515151515, "acc_norm_stderr": 0.03883565977956929 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6818181818181818, "acc_stderr": 0.033184773338453294, "acc_norm": 0.6818181818181818, "acc_norm_stderr": 0.033184773338453294 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6994818652849741, "acc_stderr": 0.033088185944157494, "acc_norm": 0.6994818652849741, "acc_norm_stderr": 0.033088185944157494 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5025641025641026, "acc_stderr": 0.025350672979412195, "acc_norm": 0.5025641025641026, "acc_norm_stderr": 0.025350672979412195 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.29259259259259257, "acc_stderr": 0.027738969632176088, "acc_norm": 0.29259259259259257, "acc_norm_stderr": 0.02773