open-llm-leaderboard-old/details_jpquiroga__Mistral_7B_ties_merge_instruct_open_orca_codeninja

该数据集是在模型jpquiroga/Mistral_7B_ties_merge_instruct_open_orca_codeninja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。数据集是从1次运行中创建的，每次运行作为每个配置中的一个特定拆分，拆分名称使用运行的时间戳。train拆分始终指向最新结果。一个额外的配置results存储了运行的所有聚合结果，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Python代码加载运行细节的示例，并包含了特定运行的最新结果。

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jpquiroga/Mistral_7B_ties_merge_instruct_open_orca_codeninja在Open LLM Leaderboard上的自动创建的。

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，每个运行在每个配置中作为一个特定的分割存在，分割名称使用运行的时间戳。
• 分割类型：每个配置包含多个分割，其中“train”分割始终指向最新的结果。
• 结果汇总：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_jpquiroga__Mistral_7B_ties_merge_instruct_open_orca_codeninja", "harness_winogrande_5", split="train")

最新结果

以下是最新结果来自2024-04-15T16:23:04.591753的摘要：

python { "all": { "acc": 0.593791278114062, "acc_stderr": 0.033151969992860686, "acc_norm": 0.5976125048945863, "acc_norm_stderr": 0.033824061944462476, "mc1": 0.4222766217870257, "mc1_stderr": 0.017290733254248174, "mc2": 0.5878025444934631, "mc2_stderr": 0.015592863615568177 }, "harness|arc:challenge|25": { "acc": 0.5674061433447098, "acc_stderr": 0.014478005694182524, "acc_norm": 0.5938566552901023, "acc_norm_stderr": 0.014351656690097862 }, "harness|hellaswag|10": { "acc": 0.6026687910774746, "acc_stderr": 0.004883455188908961, "acc_norm": 0.7994423421629158, "acc_norm_stderr": 0.003995992960088757 }, "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": 0.4888888888888889, "acc_stderr": 0.04318275491977976, "acc_norm": 0.4888888888888889, "acc_norm_stderr": 0.04318275491977976 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6381578947368421, "acc_stderr": 0.03910525752849726, "acc_norm": 0.6381578947368421, "acc_norm_stderr": 0.03910525752849726 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6792452830188679, "acc_stderr": 0.028727502957880267, "acc_norm": 0.6792452830188679, "acc_norm_stderr": 0.028727502957880267 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6458333333333334, "acc_stderr": 0.039994111357535424, "acc_norm": 0.6458333333333334, "acc_norm_stderr": 0.039994111357535424 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6011560693641619, "acc_stderr": 0.037336266553835096, "acc_norm": 0.6011560693641619, "acc_norm_stderr": 0.037336266553835096 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201943, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201943 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5063829787234042, "acc_stderr": 0.03268335899936336, "acc_norm": 0.5063829787234042, "acc_norm_stderr": 0.03268335899936336 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.37719298245614036, "acc_stderr": 0.04559522141958216, "acc_norm": 0.37719298245614036, "acc_norm_stderr": 0.04559522141958216 }, "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": 0.3968253968253968, "acc_stderr": 0.02519710107424649, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.02519710107424649 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "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": 0.7032258064516129, "acc_stderr": 0.025988500792411898, "acc_norm": 0.7032258064516129, "acc_norm_stderr": 0.025988500792411898 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4088669950738916, "acc_stderr": 0.034590588158832314, "acc_norm": 0.4088669950738916, "acc_norm_stderr": 0.034590588158832314 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7151515151515152, "acc_stderr": 0.03524390844511781, "acc_norm": 0.7151515151515152, "acc_norm_stderr": 0.03524390844511781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7676767676767676, "acc_stderr": 0.030088629490217487, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.030088629490217487 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8082901554404145, "acc_stderr": 0.02840895362624527, "acc_norm": 0.8082901554404145, "acc_norm_stderr": 0.02840895362624527 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5769230769230769, "acc_stderr": 0.025049197876042345, "acc_norm": 0.5769230769230769, "acc_norm_stderr": 0.025049197876042345 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2814814814814815, "acc_stderr": 0