open-llm-leaderboard-old/details_WebraftAI__synapsellm-7b-mistral-v0.4-preview3

该数据集是在评估模型WebraftAI/synapsellm-7b-mistral-v0.4-preview3时自动创建的，主要用于在Open LLM Leaderboard上进行评估。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1次运行生成，每次运行的结果存储为特定配置中的一个分割，分割名称使用运行的时间戳。train分割始终指向最新结果。此外，results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

该数据集是在模型 WebraftAI/synapsellm-7b-mistral-v0.4-preview3 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

数据集组成

• 数据集由 63 个配置组成，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。
• 一个额外的配置 "results" 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_WebraftAI__synapsellm-7b-mistral-v0.4-preview3", "harness_winogrande_5", split="train")

最新结果

这些是最新结果，来自 2023-12-09T20:24:42.121892 的运行（注意可能会有其他任务的结果，可以在结果和每个评估的 "latest" 分割中找到）：

python { "all": { "acc": 0.5277560649597496, "acc_stderr": 0.03425240844552933, "acc_norm": 0.532688176887894, "acc_norm_stderr": 0.034990875171934714, "mc1": 0.35862913096695226, "mc1_stderr": 0.016789289499502025, "mc2": 0.5235126569364149, "mc2_stderr": 0.015157264857162787 }, "harness|arc:challenge|25": { "acc": 0.49146757679180886, "acc_stderr": 0.014609263165632182, "acc_norm": 0.5127986348122867, "acc_norm_stderr": 0.014606603181012541 }, "harness|hellaswag|10": { "acc": 0.5513841864170484, "acc_stderr": 0.00496336208527556, "acc_norm": 0.7482573192591118, "acc_norm_stderr": 0.004331271717773856 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.43703703703703706, "acc_stderr": 0.04284958639753399, "acc_norm": 0.43703703703703706, "acc_norm_stderr": 0.04284958639753399 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.506578947368421, "acc_stderr": 0.040685900502249704, "acc_norm": 0.506578947368421, "acc_norm_stderr": 0.040685900502249704 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6264150943396226, "acc_stderr": 0.029773082713319875, "acc_norm": 0.6264150943396226, "acc_norm_stderr": 0.029773082713319875 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5416666666666666, "acc_stderr": 0.04166666666666665, "acc_norm": 0.5416666666666666, "acc_norm_stderr": 0.04166666666666665 }, "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": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5433526011560693, "acc_stderr": 0.03798106566014498, "acc_norm": 0.5433526011560693, "acc_norm_stderr": 0.03798106566014498 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.28431372549019607, "acc_stderr": 0.04488482852329017, "acc_norm": 0.28431372549019607, "acc_norm_stderr": 0.04488482852329017 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4340425531914894, "acc_stderr": 0.032400380867927465, "acc_norm": 0.4340425531914894, "acc_norm_stderr": 0.032400380867927465 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.32456140350877194, "acc_stderr": 0.04404556157374767, "acc_norm": 0.32456140350877194, "acc_norm_stderr": 0.04404556157374767 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.45517241379310347, "acc_stderr": 0.04149886942192117, "acc_norm": 0.45517241379310347, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.373015873015873, "acc_stderr": 0.02490699045899257, "acc_norm": 0.373015873015873, "acc_norm_stderr": 0.02490699045899257 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.38095238095238093, "acc_stderr": 0.043435254289490965, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.043435254289490965 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6548387096774193, "acc_stderr": 0.027045746573534327, "acc_norm": 0.6548387096774193, "acc_norm_stderr": 0.027045746573534327 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3842364532019704, "acc_stderr": 0.03422398565657551, "acc_norm": 0.3842364532019704, "acc_norm_stderr": 0.03422398565657551 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6303030303030303, "acc_stderr": 0.037694303145125674, "acc_norm": 0.6303030303030303, "acc_norm_stderr": 0.037694303145125674 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7070707070707071, "acc_stderr": 0.03242497958178815, "acc_norm": 0.7070707070707071, "acc_norm_stderr": 0.03242497958178815 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7150259067357513, "acc_stderr": 0.03257714077709662, "acc_norm": 0.7150259067357513, "acc_norm_stderr": 0.03257714077709662 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5153846153846153, "acc_stderr": 0.025339003010106515, "acc_norm": 0.5153846153846153, "acc_norm_stderr": 0.025339003010106515 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32592592592592595, "acc_stderr": 0.02857834836547307, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.02857