open-llm-leaderboard-old/details_jukofyork__Eurus-70b-sft-fixed

该数据集是在模型 jukofyork/Eurus-70b-sft-fixed 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。它包含来自 1 次运行的数据，每次运行在每个配置中表示为特定的分割，使用运行的时间戳命名。train 分割始终指向最新的结果。一个名为 results 的额外配置存储了运行的所有聚合结果，这些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 中的 datasets 库加载运行详情的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在对模型 jukofyork/Eurus-70b-sft-fixed 进行评估时自动创建的，用于 Open LLM Leaderboard。

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。
• 创建次数：数据集从1次运行中创建。每次运行在每个配置中都有一个特定的分割，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。
• 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 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_jukofyork__Eurus-70b-sft-fixed", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-16T01:31:00.510041 运行的最新结果：

python { "all": { "acc": 0.5534378911031584, "acc_stderr": 0.0340354565992681, "acc_norm": 0.5566945614499405, "acc_norm_stderr": 0.03473275366292199, "mc1": 0.3463892288861689, "mc1_stderr": 0.016656997109125136, "mc2": 0.4954641838081292, "mc2_stderr": 0.015266785797213743 }, "harness|arc:challenge|25": { "acc": 0.5051194539249146, "acc_stderr": 0.01461062489030916, "acc_norm": 0.5520477815699659, "acc_norm_stderr": 0.014532011498211674 }, "harness|hellaswag|10": { "acc": 0.5300736904999004, "acc_stderr": 0.004980747448813314, "acc_norm": 0.7333200557657837, "acc_norm_stderr": 0.004413198640053985 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "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": 0.5592105263157895, "acc_stderr": 0.04040311062490436, "acc_norm": 0.5592105263157895, "acc_norm_stderr": 0.04040311062490436 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5358490566037736, "acc_stderr": 0.030693675018458003, "acc_norm": 0.5358490566037736, "acc_norm_stderr": 0.030693675018458003 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5277777777777778, "acc_stderr": 0.04174752578923185, "acc_norm": 0.5277777777777778, "acc_norm_stderr": 0.04174752578923185 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4797687861271676, "acc_stderr": 0.03809342081273958, "acc_norm": 0.4797687861271676, "acc_norm_stderr": 0.03809342081273958 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3235294117647059, "acc_stderr": 0.046550104113196177, "acc_norm": 0.3235294117647059, "acc_norm_stderr": 0.046550104113196177 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.44680851063829785, "acc_stderr": 0.0325005368436584, "acc_norm": 0.44680851063829785, "acc_norm_stderr": 0.0325005368436584 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4473684210526316, "acc_stderr": 0.046774730044911984, "acc_norm": 0.4473684210526316, "acc_norm_stderr": 0.046774730044911984 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.46206896551724136, "acc_stderr": 0.04154659671707548, "acc_norm": 0.46206896551724136, "acc_norm_stderr": 0.04154659671707548 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42857142857142855, "acc_stderr": 0.025487187147859372, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.025487187147859372 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5193548387096775, "acc_stderr": 0.0284226874043121, "acc_norm": 0.5193548387096775, "acc_norm_stderr": 0.0284226874043121 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3891625615763547, "acc_stderr": 0.034304624161038716, "acc_norm": 0.3891625615763547, "acc_norm_stderr": 0.034304624161038716 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7393939393939394, "acc_stderr": 0.034277431758165236, "acc_norm": 0.7393939393939394, "acc_norm_stderr": 0.034277431758165236 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6313131313131313, "acc_stderr": 0.034373055019806184, "acc_norm": 0.6313131313131313, "acc_norm_stderr": 0.034373055019806184 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7616580310880829, "acc_stderr": 0.030748905363909878, "acc_norm": 0.7616580310880829, "acc_norm_stderr": 0.030748905363909878 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5384615384615384, "acc_stderr": 0.025275892070240644, "acc_norm": 0.5384615384615384, "acc_norm_stderr": 0.025275892070240644 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.35185185185185186, "acc_stderr": 0.02911661760608301, "acc_norm": 0.