open-llm-leaderboard-old/details_OpenBuddy__openbuddy-mixtral-7bx8-v16.3-32k

该数据集是在模型OpenBuddy/openbuddy-mixtral-7bx8-v16.3-32k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，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`datasets`库中的`load_dataset`函数加载运行细节的示例。README中还包含了特定运行的最新结果，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

数据集简介

该数据集是在模型 OpenBuddy/openbuddy-mixtral-7bx8-v16.3-32k 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

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_OpenBuddy__openbuddy-mixtral-7bx8-v16.3-32k", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-05T04:57:41.818907 运行的最新结果：

python { "all": { "acc": 0.6992764990088943, "acc_stderr": 0.030080190218914955, "acc_norm": 0.7136773526591422, "acc_norm_stderr": 0.030895052800428254, "mc1": 0.3953488372093023, "mc1_stderr": 0.017115815632418187, "mc2": 0.5638733199382533, "mc2_stderr": 0.014806158821537194 }, "harness|arc:challenge|25": { "acc": 0.22781569965870307, "acc_stderr": 0.01225670860232692, "acc_norm": 0.2645051194539249, "acc_norm_stderr": 0.012889272949313368 }, "harness|hellaswag|10": { "acc": 0.6227843059151563, "acc_stderr": 0.004836990373261572, "acc_norm": 0.8083051185022904, "acc_norm_stderr": 0.003928298121755031 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.48, "acc_stderr": 0.05021167315686779, "acc_norm": 0.48, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6814814814814815, "acc_stderr": 0.040247784019771096, "acc_norm": 0.6814814814814815, "acc_norm_stderr": 0.040247784019771096 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8026315789473685, "acc_stderr": 0.03238981601699397, "acc_norm": 0.8026315789473685, "acc_norm_stderr": 0.03238981601699397 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8037735849056604, "acc_stderr": 0.024442388131100827, "acc_norm": 0.8037735849056604, "acc_norm_stderr": 0.024442388131100827 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8333333333333334, "acc_stderr": 0.031164899666948617, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.031164899666948617 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6994219653179191, "acc_stderr": 0.03496101481191179, "acc_norm": 0.6994219653179191, "acc_norm_stderr": 0.03496101481191179 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5392156862745098, "acc_stderr": 0.049598599663841815, "acc_norm": 0.5392156862745098, "acc_norm_stderr": 0.049598599663841815 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6936170212765957, "acc_stderr": 0.03013590647851756, "acc_norm": 0.6936170212765957, "acc_norm_stderr": 0.03013590647851756 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6140350877192983, "acc_stderr": 0.045796394220704355, "acc_norm": 0.6140350877192983, "acc_norm_stderr": 0.045796394220704355 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7103448275862069, "acc_stderr": 0.03780019230438015, "acc_norm": 0.7103448275862069, "acc_norm_stderr": 0.03780019230438015 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.5052910052910053, "acc_stderr": 0.02574986828855657, "acc_norm": 0.5052910052910053, "acc_norm_stderr": 0.02574986828855657 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5793650793650794, "acc_stderr": 0.04415438226743745, "acc_norm": 0.5793650793650794, "acc_norm_stderr": 0.04415438226743745 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8516129032258064, "acc_stderr": 0.020222737554330378, "acc_norm": 0.8516129032258064, "acc_norm_stderr": 0.020222737554330378 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5862068965517241, "acc_stderr": 0.03465304488406796, "acc_norm": 0.5862068965517241, "acc_norm_stderr": 0.03465304488406796 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.73, "acc_stderr": 0.04461960433384739, "acc_norm": 0.73, "acc_norm_stderr": 0.04461960433384739 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8424242424242424, "acc_stderr": 0.028450388805284332, "acc_norm": 0.8424242424242424, "acc_norm_stderr": 0.028450388805284332 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8535353535353535, "acc_stderr": 0.025190921114603918, "acc_norm": 0.8535353535353535, "acc_norm_stderr": 0.025190921114603918 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9430051813471503, "acc_stderr": 0.01673108529360755, "acc_norm": 0.9430051813471503, "acc_norm_stderr": 0.01673108529360755 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7076923076923077, "acc_stderr": 0.023060438380857733, "acc_norm": 0.7076923076923077, "acc_norm_stderr": 0.023060438380857733 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3888888888888889, "acc_stderr": 0.02972