open-llm-leaderboard-old/details_AA051610__C0322-reft

该数据集是在Open LLM Leaderboard上对模型AA051610/C0322-reft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，每次运行都是每个配置中的一个特定分割，分割名称使用运行的时间戳。train分割始终指向最新的结果。此外，还有一个名为results的配置，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。文件还提供了如何使用Python代码加载运行细节的示例，并列出了特定运行的最新结果。

原始信息汇总

数据集概述

该数据集是在对模型 AA051610/C0322-reft 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

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。
• 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_AA051610__C0322-reft", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-23T11:24:04.137622 运行的最新结果：

python { "all": { "acc": 0.7834126131968995, "acc_stderr": 0.02660899546178371, "acc_norm": 0.7931618388481015, "acc_norm_stderr": 0.02706139554995661, "mc1": 0.40758873929008566, "mc1_stderr": 0.017201949234553107, "mc2": 0.5977183511445812, "mc2_stderr": 0.015244518864445982 }, "harness|arc:challenge|25": { "acc": 0.6177474402730375, "acc_stderr": 0.014200454049979275, "acc_norm": 0.64419795221843, "acc_norm_stderr": 0.013990571137918758 }, "harness|hellaswag|10": { "acc": 0.638020314678351, "acc_stderr": 0.004795908282584542, "acc_norm": 0.837382991435969, "acc_norm_stderr": 0.0036826171219143077 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.762962962962963, "acc_stderr": 0.03673731683969506, "acc_norm": 0.762962962962963, "acc_norm_stderr": 0.03673731683969506 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8881578947368421, "acc_stderr": 0.02564834125169361, "acc_norm": 0.8881578947368421, "acc_norm_stderr": 0.02564834125169361 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8301886792452831, "acc_stderr": 0.023108393799841326, "acc_norm": 0.8301886792452831, "acc_norm_stderr": 0.023108393799841326 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.9305555555555556, "acc_stderr": 0.021257974822832048, "acc_norm": 0.9305555555555556, "acc_norm_stderr": 0.021257974822832048 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.74, "acc_stderr": 0.04408440022768078, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7976878612716763, "acc_stderr": 0.03063114553919882, "acc_norm": 0.7976878612716763, "acc_norm_stderr": 0.03063114553919882 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5686274509803921, "acc_stderr": 0.04928099597287534, "acc_norm": 0.5686274509803921, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7021276595744681, "acc_stderr": 0.029896145682095455, "acc_norm": 0.7021276595744681, "acc_norm_stderr": 0.029896145682095455 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6842105263157895, "acc_stderr": 0.04372748290278007, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.04372748290278007 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7379310344827587, "acc_stderr": 0.03664666337225257, "acc_norm": 0.7379310344827587, "acc_norm_stderr": 0.03664666337225257 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.5502645502645502, "acc_stderr": 0.02562085704293665, "acc_norm": 0.5502645502645502, "acc_norm_stderr": 0.02562085704293665 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5158730158730159, "acc_stderr": 0.044698818540726076, "acc_norm": 0.5158730158730159, "acc_norm_stderr": 0.044698818540726076 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8870967741935484, "acc_stderr": 0.01800360332586361, "acc_norm": 0.8870967741935484, "acc_norm_stderr": 0.01800360332586361 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6798029556650246, "acc_stderr": 0.032826493853041504, "acc_norm": 0.6798029556650246, "acc_norm_stderr": 0.032826493853041504 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.82, "acc_stderr": 0.038612291966536955, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536955 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.9393939393939394, "acc_stderr": 0.01863202167916559, "acc_norm": 0.9393939393939394, "acc_norm_stderr": 0.01863202167916559 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9393939393939394, "acc_stderr": 0.016999994927421606, "acc_norm": 0.9393939393939394, "acc_norm_stderr": 0.016999994927421606 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9689119170984456, "acc_stderr": 0.01252531062552702, "acc_norm": 0.9689119170984456, "acc_norm_stderr": 0.01252531062552702 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8, "acc_stderr": 0.020280805062535726, "acc_norm": 0.8, "acc_norm_stderr": 0.020280805062535726 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.4925925925925926, "acc_stderr": 0.030482192395191506, "acc_norm": 0.4925925925925926, "acc_norm_stderr": 0.030482192395191506 },