open-llm-leaderboard-old/details_diffnamehard__Psyfighter2-Noromaid-ties-Capybara-13B

该数据集是在模型diffnamehard/Psyfighter2-Noromaid-ties-Capybara-13B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，每次运行在每个配置中表示为特定的分割，train分割始终指向最新结果。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中的datasets库加载运行细节的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型diffnamehard/Psyfighter2-Noromaid-ties-Capybara-13B在Open LLM Leaderboard上的运行过程中自动创建的。

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_diffnamehard__Psyfighter2-Noromaid-ties-Capybara-13B", "harness_winogrande_5", split="train")

最新结果

以下是2024-01-13T20:20:55.847857运行的最新结果：

python { "all": { "acc": 0.5664354333372791, "acc_stderr": 0.033523024960411534, "acc_norm": 0.5714502762424973, "acc_norm_stderr": 0.034221321166461816, "mc1": 0.3463892288861689, "mc1_stderr": 0.016656997109125136, "mc2": 0.5143942772336377, "mc2_stderr": 0.015015865193028501 }, "harness|arc:challenge|25": { "acc": 0.5861774744027304, "acc_stderr": 0.014392730009221009, "acc_norm": 0.6228668941979523, "acc_norm_stderr": 0.014163366896192598 }, "harness|hellaswag|10": { "acc": 0.638020314678351, "acc_stderr": 0.004795908282584543, "acc_norm": 0.8386775542720574, "acc_norm_stderr": 0.003670763673792967 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5657894736842105, "acc_stderr": 0.040335656678483205, "acc_norm": 0.5657894736842105, "acc_norm_stderr": 0.040335656678483205 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.55, "acc_stderr": 0.04999999999999999, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999999 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6075471698113207, "acc_stderr": 0.03005258057955785, "acc_norm": 0.6075471698113207, "acc_norm_stderr": 0.03005258057955785 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6111111111111112, "acc_stderr": 0.04076663253918567, "acc_norm": 0.6111111111111112, "acc_norm_stderr": 0.04076663253918567 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "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": 0.5202312138728323, "acc_stderr": 0.03809342081273957, "acc_norm": 0.5202312138728323, "acc_norm_stderr": 0.03809342081273957 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.22549019607843138, "acc_stderr": 0.041583075330832865, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.041583075330832865 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4595744680851064, "acc_stderr": 0.032579014820998356, "acc_norm": 0.4595744680851064, "acc_norm_stderr": 0.032579014820998356 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.04266339443159394, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.04266339443159394 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.496551724137931, "acc_stderr": 0.041665675771015785, "acc_norm": 0.496551724137931, "acc_norm_stderr": 0.041665675771015785 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3253968253968254, "acc_stderr": 0.024130158299762613, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.024130158299762613 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3492063492063492, "acc_stderr": 0.04263906892795132, "acc_norm": 0.3492063492063492, "acc_norm_stderr": 0.04263906892795132 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6709677419354839, "acc_stderr": 0.02672949906834996, "acc_norm": 0.6709677419354839, "acc_norm_stderr": 0.02672949906834996 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.42857142857142855, "acc_stderr": 0.03481904844438804, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.03481904844438804 }, "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": 0.6848484848484848, "acc_stderr": 0.0362773057502241, "acc_norm": 0.6848484848484848, "acc_norm_stderr": 0.0362773057502241 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7171717171717171, "acc_stderr": 0.03208779558786752, "acc_norm": 0.7171717171717171, "acc_norm_stderr": 0.03208779558786752 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8082901554404145, "acc_stderr": 0.02840895362624526, "acc_norm": 0.8082901554404145, "acc_norm_stderr": 0.02840895362624526 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5307692307692308, "acc_stderr": 0.025302958890850154, "acc_norm": 0.5307692307692308, "acc_norm_stderr": 0.025302958890850154 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.31851851851851853, "acc_stderr": 0.02840653309060846, "acc_norm": 0.3