open-llm-leaderboard-old/details_mistralai__Mixtral-8x7B-v0.1

该数据集是在评估模型mistralai/Mixtral-8x7B-v0.1时自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。数据集是从3次运行中创建的，每次运行的结果都作为一个特定的分割存储在配置中，分割的名称使用运行的时间戳。train分割始终指向最新的结果。此外，还有一个名为results的配置，存储了所有运行的聚合结果，并用于计算和显示在Open LLM Leaderboard上的聚合指标。

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mistralai/Mixtral-8x7B-v0.1在Open LLM Leaderboard上的自动创建的。

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。
• 数据集由3次运行创建，每次运行的结果可以在每个配置中找到，以运行的时间戳命名的特定分割形式存储。
• "train"分割始终指向最新的结果。
• 额外的配置"results"存储所有运行的聚合结果，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_mistralai__Mixtral-8x7B-v0.1", "harness_winogrande_5", split="train")

最新结果

这些是最新结果，来自2024-01-04T16:34:48.985318的运行： python { "all": { "acc": 0.7159135789734996, "acc_stderr": 0.02999272353761279, "acc_norm": 0.7203233140735184, "acc_norm_stderr": 0.03056866632319033, "mc1": 0.3182374541003672, "mc1_stderr": 0.01630598864892061, "mc2": 0.4680543300316138, "mc2_stderr": 0.014120170542973978 }, "harness|arc:challenge|25": { "acc": 0.6373720136518771, "acc_stderr": 0.014049106564955002, "acc_norm": 0.6638225255972696, "acc_norm_stderr": 0.013804855026205761 }, "harness|hellaswag|10": { "acc": 0.6695877315275841, "acc_stderr": 0.004694002781939571, "acc_norm": 0.8645688109938259, "acc_norm_stderr": 0.003414842236517104 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7185185185185186, "acc_stderr": 0.03885004245800254, "acc_norm": 0.7185185185185186, "acc_norm_stderr": 0.03885004245800254 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8289473684210527, "acc_stderr": 0.030643607071677098, "acc_norm": 0.8289473684210527, "acc_norm_stderr": 0.030643607071677098 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.76, "acc_stderr": 0.04292346959909283, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909283 }, "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": 0.8680555555555556, "acc_stderr": 0.02830096838204443, "acc_norm": 0.8680555555555556, "acc_norm_stderr": 0.02830096838204443 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "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": 0.6994219653179191, "acc_stderr": 0.03496101481191179, "acc_norm": 0.6994219653179191, "acc_norm_stderr": 0.03496101481191179 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.46078431372549017, "acc_stderr": 0.04959859966384181, "acc_norm": 0.46078431372549017, "acc_norm_stderr": 0.04959859966384181 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.039427724440366234, "acc_norm": 0.81, "acc_norm_stderr": 0.039427724440366234 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6808510638297872, "acc_stderr": 0.030472973363380035, "acc_norm": 0.6808510638297872, "acc_norm_stderr": 0.030472973363380035 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6491228070175439, "acc_stderr": 0.04489539350270698, "acc_norm": 0.6491228070175439, "acc_norm_stderr": 0.04489539350270698 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6896551724137931, "acc_stderr": 0.03855289616378948, "acc_norm": 0.6896551724137931, "acc_norm_stderr": 0.03855289616378948 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.48148148148148145, "acc_stderr": 0.025733641991838987, "acc_norm": 0.48148148148148145, "acc_norm_stderr": 0.025733641991838987 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5634920634920635, "acc_stderr": 0.04435932892851466, "acc_norm": 0.5634920634920635, "acc_norm_stderr": 0.04435932892851466 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8419354838709677, "acc_stderr": 0.020752831511875274, "acc_norm": 0.8419354838709677, "acc_norm_stderr": 0.020752831511875274 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6354679802955665, "acc_stderr": 0.0338640574606209, "acc_norm": 0.6354679802955665, "acc_norm_stderr": 0.0338640574606209 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8181818181818182, "acc_stderr": 0.030117688929503585, "acc_norm": 0.8181818181818182, "acc_norm_stderr": 0.030117688929503585 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9378238341968912, "acc_stderr": 0.017426974154240524, "acc_norm": 0.9378238341968912, "acc_norm_stderr": 0.017426974154240524 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7051282051282052, "acc_stderr": 0.0231193627582323, "acc_norm": 0.7051282051282052, "acc_norm_stderr": 0.0231193627582323 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3851851851851852, "acc_stderr": 0.029670906124630886, "acc_norm": 0.3851851851851852, "acc_norm_stderr": 0.029670906124630886 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.7857142857142857,