open-llm-leaderboard-old/details_KoboldAI__Mixtral-8x7B-Holodeck-v1

该数据集是在评估模型KoboldAI/Mixtral-8x7B-Holodeck-v1时自动创建的，评估是在Open LLM Leaderboard上进行的。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1次运行中创建的，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。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Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集摘要

该数据集是在评估模型 KoboldAI/Mixtral-8x7B-Holodeck-v1 在 Open LLM Leaderboard 上的自动创建的。数据集包含 63 个配置，每个配置对应一个评估任务。

数据集结构

• 配置数量: 63
• 创建来源: 1 次运行
• 数据分割: 每个配置包含特定运行的分割，分割名称使用运行的时间戳。"train" 分割指向最新的结果。
• 额外配置: "results" 配置存储所有运行的聚合结果，用于计算和显示聚合指标在 Open LLM Leaderboard 上。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_KoboldAI__Mixtral-8x7B-Holodeck-v1", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-08T01:48:17.297315 运行的最新结果：

python { "all": { "acc": 0.7134257804439076, "acc_stderr": 0.030058748528777976, "acc_norm": 0.7183525568245921, "acc_norm_stderr": 0.030631711241976504, "mc1": 0.31334149326805383, "mc1_stderr": 0.01623806506905961, "mc2": 0.48282128629443755, "mc2_stderr": 0.014218563548108439 }, "harness|arc:challenge|25": { "acc": 0.6254266211604096, "acc_stderr": 0.014144193471893463, "acc_norm": 0.6655290102389079, "acc_norm_stderr": 0.013787460322441379 }, "harness|hellaswag|10": { "acc": 0.6700856403106951, "acc_stderr": 0.004692208279690597, "acc_norm": 0.867755427205736, "acc_norm_stderr": 0.0033806414709899235 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6962962962962963, "acc_stderr": 0.03972552884785137, "acc_norm": 0.6962962962962963, "acc_norm_stderr": 0.03972552884785137 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8092105263157895, "acc_stderr": 0.031975658210325, "acc_norm": 0.8092105263157895, "acc_norm_stderr": 0.031975658210325 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.71, "acc_stderr": 0.04560480215720684, "acc_norm": 0.71, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7924528301886793, "acc_stderr": 0.024959918028911274, "acc_norm": 0.7924528301886793, "acc_norm_stderr": 0.024959918028911274 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8541666666666666, "acc_stderr": 0.02951424596429177, "acc_norm": 0.8541666666666666, "acc_norm_stderr": 0.02951424596429177 }, "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": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7109826589595376, "acc_stderr": 0.034564257450869995, "acc_norm": 0.7109826589595376, "acc_norm_stderr": 0.034564257450869995 }, "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": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6723404255319149, "acc_stderr": 0.030683020843231008, "acc_norm": 0.6723404255319149, "acc_norm_stderr": 0.030683020843231008 }, "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": 0.696551724137931, "acc_stderr": 0.038312260488503336, "acc_norm": 0.696551724137931, "acc_norm_stderr": 0.038312260488503336 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.48412698412698413, "acc_stderr": 0.025738330639412152, "acc_norm": 0.48412698412698413, "acc_norm_stderr": 0.025738330639412152 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5476190476190477, "acc_stderr": 0.044518079590553275, "acc_norm": 0.5476190476190477, "acc_norm_stderr": 0.044518079590553275 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8354838709677419, "acc_stderr": 0.02109084774593931, "acc_norm": 0.8354838709677419, "acc_norm_stderr": 0.02109084774593931 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6305418719211823, "acc_stderr": 0.03395970381998574, "acc_norm": 0.6305418719211823, "acc_norm_stderr": 0.03395970381998574 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8242424242424242, "acc_stderr": 0.02972094300622445, "acc_norm": 0.8242424242424242, "acc_norm_stderr": 0.02972094300622445 }, "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": 0.9481865284974094, "acc_stderr": 0.01599622932024412, "acc_norm": 0.9481865284974094, "acc_norm_stderr": 0.01599622932024412 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7025641025641025, "acc_stderr": 0.023177408131465942, "acc_norm": 0.7025641025641025, "acc_norm_stderr": 0.023177408131465942 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.37777777777777777, "acc_stderr": 0.029560707392465718,