open-llm-leaderboard-old/details_JunchengXie__Mistral-7B-Instruct-v0.2-gpt-4-80k

该数据集是在模型JunchengXie/Mistral-7B-Instruct-v0.2-gpt-4-80k在Open LLM Leaderboard上进行评估时自动生成的。数据集包含63个配置，每个配置对应一个被评估的任务。数据集由一次运行生成，每次运行作为一个特定的分割，分割名称由运行的时间戳命名。train分割始终指向最新的结果。此外，还有一个results配置存储了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。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

数据集简介

该数据集是在评估模型JunchengXie/Mistral-7B-Instruct-v0.2-gpt-4-80k在Open LLM Leaderboard上的运行过程中自动创建的。

数据集结构

• 配置数量：63个配置，每个配置对应一个评估任务。
• 数据来源：数据集来自1次运行，每个运行结果作为一个特定的分割存储在每个配置中，分割名称使用运行的时间戳。
• 最新结果："train"分割始终指向最新的结果。
• 汇总结果：一个额外的配置"results"存储所有运行的汇总结果，用于计算和显示在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_JunchengXie__Mistral-7B-Instruct-v0.2-gpt-4-80k", "harness_winogrande_5", split="train")

最新结果

以下是2024-03-14T09:04:41.139989的最新结果：

python { "all": { "acc": 0.6069080123338292, "acc_stderr": 0.033050604752592964, "acc_norm": 0.6121049072824598, "acc_norm_stderr": 0.033720220585086495, "mc1": 0.4602203182374541, "mc1_stderr": 0.01744801722396088, "mc2": 0.6394631048375904, "mc2_stderr": 0.015157653750037884 }, "harness|arc:challenge|25": { "acc": 0.5520477815699659, "acc_stderr": 0.014532011498211678, "acc_norm": 0.5802047781569966, "acc_norm_stderr": 0.01442218122630303 }, "harness|hellaswag|10": { "acc": 0.5894244174467238, "acc_stderr": 0.0049093289929150775, "acc_norm": 0.788886675960964, "acc_norm_stderr": 0.004072645874992216 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6447368421052632, "acc_stderr": 0.038947344870133176, "acc_norm": 0.6447368421052632, "acc_norm_stderr": 0.038947344870133176 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6754716981132075, "acc_stderr": 0.02881561571343211, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.02881561571343211 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6875, "acc_stderr": 0.038760854559127644, "acc_norm": 0.6875, "acc_norm_stderr": 0.038760854559127644 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6011560693641619, "acc_stderr": 0.0373362665538351, "acc_norm": 0.6011560693641619, "acc_norm_stderr": 0.0373362665538351 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4215686274509804, "acc_stderr": 0.04913595201274498, "acc_norm": 0.4215686274509804, "acc_norm_stderr": 0.04913595201274498 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.73, "acc_stderr": 0.0446196043338474, "acc_norm": 0.73, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.548936170212766, "acc_stderr": 0.032529096196131965, "acc_norm": 0.548936170212766, "acc_norm_stderr": 0.032529096196131965 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.40350877192982454, "acc_stderr": 0.046151869625837026, "acc_norm": 0.40350877192982454, "acc_norm_stderr": 0.046151869625837026 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555497, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555497 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3862433862433862, "acc_stderr": 0.025075981767601684, "acc_norm": 0.3862433862433862, "acc_norm_stderr": 0.025075981767601684 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.0437588849272706, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.0437588849272706 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6225806451612903, "acc_stderr": 0.02757596072327824, "acc_norm": 0.6225806451612903, "acc_norm_stderr": 0.02757596072327824 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5221674876847291, "acc_stderr": 0.03514528562175008, "acc_norm": 0.5221674876847291, "acc_norm_stderr": 0.03514528562175008 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7090909090909091, "acc_stderr": 0.03546563019624336, "acc_norm": 0.7090909090909091, "acc_norm_stderr": 0.03546563019624336 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7474747474747475, "acc_stderr": 0.030954055470365897, "acc_norm": 0.7474747474747475, "acc_norm_stderr": 0.030954055470365897 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8497409326424871, "acc_stderr": 0.025787723180723872, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.025787723180723872 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.558974358974359, "acc_stderr": 0.02517404838400074, "acc_norm": 0.558974358974359, "acc_norm_stderr": 0.02517404838400074 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.31851851851851853, "acc_stderr": 0.028406533090608452, "acc_norm":