open-llm-leaderboard-old/details_aihub-app__zyte-1.1b

该数据集是在Open LLM Leaderboard上对模型aihub-app/zyte-1.1B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。数据集由2次运行生成，每次运行的结果作为特定配置中的一个分割，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，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。

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 aihub-app/zyte-1.1B 在 Open LLM Leaderboard 上的运行过程中自动创建的。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 2 次运行结果组成，每次运行的详细结果可以在每个配置中找到，以运行的时间戳命名的特定分片形式存储。"train" 分片始终指向最新的结果。

数据加载示例

以下是加载特定运行详细结果的示例代码： python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_aihub-app__zyte-1.1B", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-11T05:23:20.715218 运行 的最新结果： python { "all": { "acc": 0.25361868916315616, "acc_stderr": 0.030573314410780546, "acc_norm": 0.2546801684169431, "acc_norm_stderr": 0.031326823208064805, "mc1": 0.2729498164014688, "mc1_stderr": 0.015594753632006533, "mc2": 0.42145545716321137, "mc2_stderr": 0.014685756302738077 }, "harness|arc:challenge|25": { "acc": 0.34726962457337884, "acc_stderr": 0.013913034529620434, "acc_norm": 0.378839590443686, "acc_norm_stderr": 0.014175915490000324 }, "harness|hellaswag|10": { "acc": 0.45668193586934874, "acc_stderr": 0.0049710199427265775, "acc_norm": 0.6137223660625374, "acc_norm_stderr": 0.004859004184694623 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.28888888888888886, "acc_stderr": 0.0391545063041425, "acc_norm": 0.28888888888888886, "acc_norm_stderr": 0.0391545063041425 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.20394736842105263, "acc_stderr": 0.032790004063100515, "acc_norm": 0.20394736842105263, "acc_norm_stderr": 0.032790004063100515 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.18, "acc_stderr": 0.03861229196653695, "acc_norm": 0.18, "acc_norm_stderr": 0.03861229196653695 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.2188679245283019, "acc_stderr": 0.025447863825108625, "acc_norm": 0.2188679245283019, "acc_norm_stderr": 0.025447863825108625 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.25, "acc_stderr": 0.03621034121889507, "acc_norm": 0.25, "acc_norm_stderr": 0.03621034121889507 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "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": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.18497109826589594, "acc_stderr": 0.029605623981771214, "acc_norm": 0.18497109826589594, "acc_norm_stderr": 0.029605623981771214 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2549019607843137, "acc_stderr": 0.043364327079931785, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.043364327079931785 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.2723404255319149, "acc_stderr": 0.0291012906983867, "acc_norm": 0.2723404255319149, "acc_norm_stderr": 0.0291012906983867 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.15789473684210525, "acc_stderr": 0.034302659784856984, "acc_norm": 0.15789473684210525, "acc_norm_stderr": 0.034302659784856984 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.2482758620689655, "acc_stderr": 0.03600105692727772, "acc_norm": 0.2482758620689655, "acc_norm_stderr": 0.03600105692727772 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.23809523809523808, "acc_stderr": 0.021935878081184756, "acc_norm": 0.23809523809523808, "acc_norm_stderr": 0.021935878081184756 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.16666666666666666, "acc_stderr": 0.03333333333333338, "acc_norm": 0.16666666666666666, "acc_norm_stderr": 0.03333333333333338 }, "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": 0.32, "acc_stderr": 0.04688261722621503, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621503 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.22424242424242424, "acc_stderr": 0.03256866661681102, "acc_norm": 0.22424242424242424, "acc_norm_stderr": 0.03256866661681102 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.22727272727272727, "acc_stderr": 0.029857515673386407, "acc_norm": 0.22727272727272727, "acc_norm_stderr": 0.029857515673386407 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.21243523316062177, "acc_stderr": 0.029519282616817244, "acc_norm": 0.21243523316062177, "acc_norm_stderr": 0.029519282616817244 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.2512820512820513, "acc_stderr": 0.021992016662370547, "acc_norm": 0.2512820512820513, "acc_norm_stderr": 0.021992016662370547 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.21851851851851853, "acc_stderr": 0.025195752251823796, "acc_norm": 0.21851851851851853, "acc_norm_stderr": 0.025195752251823796 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.23949579831932774, "acc