open-llm-leaderboard-old/details_freecs__ThetaWave-7B-v0

该数据集是在模型 freecs/ThetaWave-7B-v0 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，每个配置对应于一个评估任务。它包含 1 次运行的结果，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 还提供了一个示例，展示了如何使用 `datasets` 库中的 `load_dataset` 函数加载运行中的详细信息。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型freecs/ThetaWave-7B-v0的评估运行期间自动创建的，用于Open LLM Leaderboard。数据集包含63个配置，每个配置对应一个评估任务。

数据集结构

数据集由1次运行创建，每个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。

额外配置

一个额外的配置"results"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。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_freecs__ThetaWave-7B-v0", "harness_winogrande_5", split="train")

最新结果

这些是最新结果（来自2024-01-18T21:58:24.571103运行）的摘要：

python { "all": { "acc": 0.6139427832716801, "acc_stderr": 0.0329772926223431, "acc_norm": 0.6160760841456204, "acc_norm_stderr": 0.033642251011914065, "mc1": 0.47123623011015914, "mc1_stderr": 0.01747451384852552, "mc2": 0.6156128002968497, "mc2_stderr": 0.015661943081276854 }, "harness|arc:challenge|25": { "acc": 0.6339590443686007, "acc_stderr": 0.014077223108470142, "acc_norm": 0.6851535836177475, "acc_norm_stderr": 0.01357265770308495 }, "harness|hellaswag|10": { "acc": 0.6622186815375424, "acc_stderr": 0.004719870074967247, "acc_norm": 0.8535152360087632, "acc_norm_stderr": 0.0035286889976580537 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6644736842105263, "acc_stderr": 0.038424985593952694, "acc_norm": 0.6644736842105263, "acc_norm_stderr": 0.038424985593952694 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7018867924528301, "acc_stderr": 0.02815283794249387, "acc_norm": 0.7018867924528301, "acc_norm_stderr": 0.02815283794249387 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7152777777777778, "acc_stderr": 0.037738099906869334, "acc_norm": 0.7152777777777778, "acc_norm_stderr": 0.037738099906869334 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6127167630057804, "acc_stderr": 0.037143259063020656, "acc_norm": 0.6127167630057804, "acc_norm_stderr": 0.037143259063020656 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.35294117647058826, "acc_stderr": 0.04755129616062946, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.04755129616062946 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.0440844002276808, "acc_norm": 0.74, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5276595744680851, "acc_stderr": 0.03263597118409769, "acc_norm": 0.5276595744680851, "acc_norm_stderr": 0.03263597118409769 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4298245614035088, "acc_stderr": 0.04657047260594963, "acc_norm": 0.4298245614035088, "acc_norm_stderr": 0.04657047260594963 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5517241379310345, "acc_stderr": 0.04144311810878151, "acc_norm": 0.5517241379310345, "acc_norm_stderr": 0.04144311810878151 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4126984126984127, "acc_stderr": 0.02535574126305527, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.02535574126305527 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4444444444444444, "acc_stderr": 0.044444444444444495, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.044444444444444495 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5741935483870968, "acc_stderr": 0.028129112709165894, "acc_norm": 0.5741935483870968, "acc_norm_stderr": 0.028129112709165894 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.42857142857142855, "acc_stderr": 0.034819048444388045, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.034819048444388045 }, "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": 0.7757575757575758, "acc_stderr": 0.03256866661681102, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.03256866661681102 }, "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": 0.8497409326424871, "acc_stderr": 0.02578772318072388, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.02578772318072388 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6102564102564103, "acc_stderr": 0.024726967886647078, "acc_norm": 0.6102564102564103, "acc_norm_stderr": 0.024726967886647078 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.337037037037037, "acc_stderr": 0.028820884666253255, "acc_norm": 0.337037037037037, "acc_norm_stderr": 0.028820884666253255 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6218487394957983, "acc_stderr": 0.03149930577784906, "acc_norm": 0.6218