open-llm-leaderboard-old/details_fblgit__UNAversal-8x7B-v1beta

该数据集是在模型fblgit/UNAversal-8x7B-v1beta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。train分割始终指向最新结果。一个名为results的额外配置存储了所有运行的聚合结果，这些结果用于计算和显示Open LLM Leaderboard上的聚合指标。文件还提供了如何使用Python中的datasets库加载运行详情的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 fblgit/UNAversal-8x7B-v1beta 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_fblgit__UNAversal-8x7B-v1beta", "harness_winogrande_5", split="train")

最新结果

以下是 2023-12-29T13:58:56.197433 运行的最新结果：

python { "all": { "acc": 0.7032492612287039, "acc_stderr": 0.030561796046539372, "acc_norm": 0.7065688663962248, "acc_norm_stderr": 0.031159122709878497, "mc1": 0.5581395348837209, "mc1_stderr": 0.01738476747898621, "mc2": 0.7196624359754553, "mc2_stderr": 0.014067882788111132 }, "harness|arc:challenge|25": { "acc": 0.6629692832764505, "acc_stderr": 0.01381347665290228, "acc_norm": 0.6979522184300341, "acc_norm_stderr": 0.013417519144716413 }, "harness|hellaswag|10": { "acc": 0.6781517625970922, "acc_stderr": 0.00466230339523962, "acc_norm": 0.8689504082852022, "acc_norm_stderr": 0.0033676492203621095 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6888888888888889, "acc_stderr": 0.03999262876617721, "acc_norm": 0.6888888888888889, "acc_norm_stderr": 0.03999262876617721 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7828947368421053, "acc_stderr": 0.03355045304882924, "acc_norm": 0.7828947368421053, "acc_norm_stderr": 0.03355045304882924 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7849056603773585, "acc_stderr": 0.02528839450289137, "acc_norm": 0.7849056603773585, "acc_norm_stderr": 0.02528839450289137 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8194444444444444, "acc_stderr": 0.032166008088022675, "acc_norm": 0.8194444444444444, "acc_norm_stderr": 0.032166008088022675 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.63, "acc_stderr": 0.048523658709391, "acc_norm": 0.63, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7283236994219653, "acc_stderr": 0.03391750322321659, "acc_norm": 0.7283236994219653, "acc_norm_stderr": 0.03391750322321659 }, "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": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6638297872340425, "acc_stderr": 0.030881618520676942, "acc_norm": 0.6638297872340425, "acc_norm_stderr": 0.030881618520676942 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6052631578947368, "acc_stderr": 0.04598188057816542, "acc_norm": 0.6052631578947368, "acc_norm_stderr": 0.04598188057816542 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6275862068965518, "acc_stderr": 0.04028731532947558, "acc_norm": 0.6275862068965518, "acc_norm_stderr": 0.04028731532947558 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.48677248677248675, "acc_stderr": 0.025742297289575142, "acc_norm": 0.48677248677248675, "acc_norm_stderr": 0.025742297289575142 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5238095238095238, "acc_stderr": 0.04467062628403273, "acc_norm": 0.5238095238095238, "acc_norm_stderr": 0.04467062628403273 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8354838709677419, "acc_stderr": 0.021090847745939317, "acc_norm": 0.8354838709677419, "acc_norm_stderr": 0.021090847745939317 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5763546798029556, "acc_stderr": 0.03476725747649038, "acc_norm": 0.5763546798029556, "acc_norm_stderr": 0.03476725747649038 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.74, "acc_stderr": 0.044084400227680794, "acc_norm": 0.74, "acc_norm_stderr": 0.044084400227680794 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7696969696969697, "acc_stderr": 0.0328766675860349, "acc_norm": 0.7696969696969697, "acc_norm_stderr": 0.0328766675860349 }, "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": 0.01673108529360757, "acc_norm": 0.9430051813471503, "acc_norm_stderr": 0.01673108529360757 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6923076923076923, "acc_stderr": 0.02340092891831049, "acc_norm": 0.6923076923076923, "acc_norm_stderr": 0.02340092891831049 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.37407407407407406, "acc_stderr": 0.02950286112895529, "acc_norm": 0.37407407407407406, "