open-llm-leaderboard-old/details_phanerozoic__Tiny-Cowboy-1.1b-v0.1

该数据集是在对模型phanerozoic/Tiny-Cowboy-1.1b-v0.1进行评估时自动创建的，包含63个配置，每个配置对应一个评估任务。数据集由一次运行创建，每个运行都有特定的分割，以运行的时间戳命名。此外，还有一个名为"results"的配置，用于存储所有聚合的运行结果。数据集的主要用途是计算和显示在Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

该数据集是在评估模型 phanerozoic/Tiny-Cowboy-1.1b-v0.1 在 Open LLM Leaderboard 上的自动创建的。

数据集组成

• 数据集包含 63 个配置，每个配置对应一个评估任务。
• 数据集从 1 次运行中创建，每次运行可以在每个配置中找到特定的拆分，拆分名称使用运行的时间戳。
• "train" 拆分始终指向最新的结果。
• 额外的 "results" 配置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。

加载数据集示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_phanerozoic__Tiny-Cowboy-1.1b-v0.1", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-03T10:04:41.755188 运行的最新结果：

python { "all": { "acc": 0.24902738741721403, "acc_stderr": 0.03030069486926739, "acc_norm": 0.25013794446501025, "acc_norm_stderr": 0.031037525212403553, "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757444, "mc2": 0.361515716157564, "mc2_stderr": 0.013592645933761412 }, "harness|arc:challenge|25": { "acc": 0.32849829351535836, "acc_stderr": 0.013724978465537375, "acc_norm": 0.36177474402730375, "acc_norm_stderr": 0.014041957945038075 }, "harness|hellaswag|10": { "acc": 0.4482174865564629, "acc_stderr": 0.004962949784236047, "acc_norm": 0.6004779924317865, "acc_norm_stderr": 0.004887991225950264 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.18, "acc_stderr": 0.03861229196653695, "acc_norm": 0.18, "acc_norm_stderr": 0.03861229196653695 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.14074074074074075, "acc_stderr": 0.030041362609516883, "acc_norm": 0.14074074074074075, "acc_norm_stderr": 0.030041362609516883 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.17105263157894737, "acc_stderr": 0.030643607071677088, "acc_norm": 0.17105263157894737, "acc_norm_stderr": 0.030643607071677088 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.23773584905660378, "acc_stderr": 0.02619980880756191, "acc_norm": 0.23773584905660378, "acc_norm_stderr": 0.02619980880756191 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.19444444444444445, "acc_stderr": 0.033096151770590054, "acc_norm": 0.19444444444444445, "acc_norm_stderr": 0.033096151770590054 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.2, "acc_stderr": 0.040201512610368445, "acc_norm": 0.2, "acc_norm_stderr": 0.040201512610368445 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.26, "acc_stderr": 0.044084400227680794, "acc_norm": 0.26, "acc_norm_stderr": 0.044084400227680794 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.2254335260115607, "acc_stderr": 0.03186209851641144, "acc_norm": 0.2254335260115607, "acc_norm_stderr": 0.03186209851641144 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.23529411764705882, "acc_stderr": 0.04220773659171452, "acc_norm": 0.23529411764705882, "acc_norm_stderr": 0.04220773659171452 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.28, "acc_stderr": 0.04512608598542127, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.23829787234042554, "acc_stderr": 0.02785125297388977, "acc_norm": 0.23829787234042554, "acc_norm_stderr": 0.02785125297388977 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.22807017543859648, "acc_stderr": 0.03947152782669415, "acc_norm": 0.22807017543859648, "acc_norm_stderr": 0.03947152782669415 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.20689655172413793, "acc_stderr": 0.03375672449560554, "acc_norm": 0.20689655172413793, "acc_norm_stderr": 0.03375672449560554 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.23544973544973544, "acc_stderr": 0.021851509822031722, "acc_norm": 0.23544973544973544, "acc_norm_stderr": 0.021851509822031722 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2222222222222222, "acc_stderr": 0.037184890068181146, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.037184890068181146 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.2, "acc_stderr": 0.040201512610368466, "acc_norm": 0.2, "acc_norm_stderr": 0.040201512610368466 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.1967741935483871, "acc_stderr": 0.022616409420742018, "acc_norm": 0.1967741935483871, "acc_norm_stderr": 0.022616409420742018 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2019704433497537, "acc_stderr": 0.028247350122180277, "acc_norm": 0.2019704433497537, "acc_norm_stderr": 0.028247350122180277 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.22, "acc_stderr": 0.0416333199893227, "acc_norm": 0.22, "acc_norm_stderr": 0.0416333199893227 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.20606060606060606, "acc_stderr": 0.031584153240477086, "acc_norm": 0.20606060606060606, "acc_norm_stderr": 0.031584153240477086 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.21717171717171718, "acc_stderr": 0.029376616484945633, "acc_norm": 0.21717171717171718, "acc_norm_stderr": 0.029376616484945633 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.23834196891191708, "acc_stderr": 0.03074890536390989, "acc_norm": 0.23834196891191708, "acc_norm_stderr": 0.03074890536390989 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.23076923076923078, "acc_stderr": 0.02136202772522272, "acc_norm": 0.23076923076923078, "acc_norm_stderr": 0.02136202772522272 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.24814814814814815, "acc_stderr": 0.0263357