open-llm-leaderboard-old/details_xriminact__TarsDolly

该数据集是在Open LLM Leaderboard上对模型xriminact/TarsDolly进行评估时自动创建的。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1次运行中创建的，每次运行在每个配置中作为一个特定的分割存在，train分割始终指向最新结果。此外，还有一个results配置存储了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。README文件还包含了如何加载运行细节的说明，并提供了特定运行的最新结果。

原始信息汇总

数据集概述

该数据集是在模型 xriminact/TarsDolly 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。

数据集结构

• 配置数量：63
• 数据来源：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" 分割始终指向最新结果。
• 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_xriminact__TarsDolly", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-02T06:25:30.533704 运行的最新结果：

python { "all": { "acc": 0.559209839212876, "acc_stderr": 0.03381204531755427, "acc_norm": 0.5674682510835656, "acc_norm_stderr": 0.034594842292962974, "mc1": 0.28518971848225216, "mc1_stderr": 0.015805827874454892, "mc2": 0.4229222915105855, "mc2_stderr": 0.014867729775892005 }, "harness|arc:challenge|25": { "acc": 0.5520477815699659, "acc_stderr": 0.014532011498211672, "acc_norm": 0.5930034129692833, "acc_norm_stderr": 0.014356399418009128 }, "harness|hellaswag|10": { "acc": 0.6265684126667994, "acc_stderr": 0.004827266662144028, "acc_norm": 0.8184624576777534, "acc_norm_stderr": 0.0038467514306295414 }, "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": 0.4888888888888889, "acc_stderr": 0.04318275491977976, "acc_norm": 0.4888888888888889, "acc_norm_stderr": 0.04318275491977976 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5657894736842105, "acc_stderr": 0.04033565667848319, "acc_norm": 0.5657894736842105, "acc_norm_stderr": 0.04033565667848319 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6226415094339622, "acc_stderr": 0.029832808114796005, "acc_norm": 0.6226415094339622, "acc_norm_stderr": 0.029832808114796005 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6597222222222222, "acc_stderr": 0.039621355734862175, "acc_norm": 0.6597222222222222, "acc_norm_stderr": 0.039621355734862175 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5028901734104047, "acc_stderr": 0.038124005659748335, "acc_norm": 0.5028901734104047, "acc_norm_stderr": 0.038124005659748335 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201942, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201942 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.67, "acc_stderr": 0.04725815626252607, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252607 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5234042553191489, "acc_stderr": 0.03265019475033582, "acc_norm": 0.5234042553191489, "acc_norm_stderr": 0.03265019475033582 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.41228070175438597, "acc_stderr": 0.046306532033665956, "acc_norm": 0.41228070175438597, "acc_norm_stderr": 0.046306532033665956 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482758, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482758 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3941798941798942, "acc_stderr": 0.02516798233389414, "acc_norm": 0.3941798941798942, "acc_norm_stderr": 0.02516798233389414 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3412698412698413, "acc_stderr": 0.04240799327574925, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.04240799327574925 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6774193548387096, "acc_stderr": 0.02659308451657226, "acc_norm": 0.6774193548387096, "acc_norm_stderr": 0.02659308451657226 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.45320197044334976, "acc_stderr": 0.03502544650845872, "acc_norm": 0.45320197044334976, "acc_norm_stderr": 0.03502544650845872 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6727272727272727, "acc_stderr": 0.03663974994391244, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.03663974994391244 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6767676767676768, "acc_stderr": 0.03332299921070646, "acc_norm": 0.6767676767676768, "acc_norm_stderr": 0.03332299921070646 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7772020725388601, "acc_stderr": 0.03003114797764154, "acc_norm": 0.7772020725388601, "acc_norm_stderr": 0.03003114797764154 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5692307692307692, "acc_stderr": 0.025106820660539753, "acc_norm": 0.5692307692307692, "acc_norm_stderr": 0.025106820660539753 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2962962962962963, "acc_stderr": 0.027840811495871927, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.02