open-llm-leaderboard-old/details_h2m__mhm-7b-v1.3-DPO-1

该数据集是在模型 h2m/mhm-7b-v1.3-DPO-1 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，每个配置对应一个评估任务。它包含一次运行的结果，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。一个名为 results 的附加配置存储了运行的所有聚合结果，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 Hugging Face datasets 库加载数据集的示例。

原始信息汇总

数据集概述

数据集摘要

该数据集是在对模型 h2m/mhm-7b-v1.3-DPO-1 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，每次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_h2m__mhm-7b-v1.3-DPO-1", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-17T06:45:52.399769 运行的最新结果：

python { "all": { "acc": 0.45614037821682546, "acc_stderr": 0.03454781614962824, "acc_norm": 0.46207531178088435, "acc_norm_stderr": 0.035314919445415614, "mc1": 0.29253365973072215, "mc1_stderr": 0.015925597445286165, "mc2": 0.4588457171247393, "mc2_stderr": 0.015385039501663943 }, "harness|arc:challenge|25": { "acc": 0.46245733788395904, "acc_stderr": 0.01457014449507558, "acc_norm": 0.49573378839590443, "acc_norm_stderr": 0.014610858923956948 }, "harness|hellaswag|10": { "acc": 0.5036845249950209, "acc_stderr": 0.00498964592981145, "acc_norm": 0.6810396335391357, "acc_norm_stderr": 0.004651211311633843 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.23, "acc_stderr": 0.042295258468165044, "acc_norm": 0.23, "acc_norm_stderr": 0.042295258468165044 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4222222222222222, "acc_stderr": 0.042667634040995814, "acc_norm": 0.4222222222222222, "acc_norm_stderr": 0.042667634040995814 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.46710526315789475, "acc_stderr": 0.040601270352363966, "acc_norm": 0.46710526315789475, "acc_norm_stderr": 0.040601270352363966 }, "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": 0.4830188679245283, "acc_stderr": 0.030755120364119905, "acc_norm": 0.4830188679245283, "acc_norm_stderr": 0.030755120364119905 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3541666666666667, "acc_stderr": 0.039994111357535424, "acc_norm": 0.3541666666666667, "acc_norm_stderr": 0.039994111357535424 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4393063583815029, "acc_stderr": 0.03784271932887467, "acc_norm": 0.4393063583815029, "acc_norm_stderr": 0.03784271932887467 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.27450980392156865, "acc_stderr": 0.044405219061793275, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.044405219061793275 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.33191489361702126, "acc_stderr": 0.030783736757745664, "acc_norm": 0.33191489361702126, "acc_norm_stderr": 0.030783736757745664 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.34210526315789475, "acc_stderr": 0.04462917535336936, "acc_norm": 0.34210526315789475, "acc_norm_stderr": 0.04462917535336936 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4206896551724138, "acc_stderr": 0.0411391498118926, "acc_norm": 0.4206896551724138, "acc_norm_stderr": 0.0411391498118926 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3306878306878307, "acc_stderr": 0.024229965298425075, "acc_norm": 0.3306878306878307, "acc_norm_stderr": 0.024229965298425075 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.29365079365079366, "acc_stderr": 0.04073524322147126, "acc_norm": 0.29365079365079366, "acc_norm_stderr": 0.04073524322147126 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.49032258064516127, "acc_stderr": 0.02843867799890955, "acc_norm": 0.49032258064516127, "acc_norm_stderr": 0.02843867799890955 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3448275862068966, "acc_stderr": 0.03344283744280458, "acc_norm": 0.3448275862068966, "acc_norm_stderr": 0.03344283744280458 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.52, "acc_stderr": 0.05021167315686779, "acc_norm": 0.52, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5878787878787879, "acc_stderr": 0.03843566993588716, "acc_norm": 0.5878787878787879, "acc_norm_stderr": 0.03843566993588716 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5959595959595959, "acc_stderr": 0.03496130972056128, "acc_norm": 0.5959595959595959, "acc_norm_stderr": 0.03496130972056128 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6113989637305699, "acc_stderr": 0.035177397963731316, "acc_norm": 0.6113989637305699, "acc_norm_stderr": 0.035177397963731316 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4358974358974359, "acc_stderr": 0.025141801511177495, "acc_norm": 0.4358974358974359, "acc_norm_stderr": 0.025141801511177495 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.24074074074074073, "acc_stderr": 0.0260671