open-llm-leaderboard-old/details_DatPySci__pythia-1b-kto-iter0

该数据集是在模型 DatPySci/pythia-1b-kto-iter0 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。数据集是从一次或多次运行中生成的，每次运行都作为每个配置中的特定分割存储。train 分割始终指向最新结果。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 还提供了如何使用 `datasets` 库中的 `load_dataset` 函数加载数据集的示例。README 中还包含了特定运行的最新结果，显示了不同任务的各种指标，如准确率和标准误差。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型DatPySci/pythia-1b-kto-iter0在Open LLM Leaderboard上的评估运行期间自动创建的。

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。
• 数据集由1次运行创建，每个运行可以在每个配置中作为一个特定的分片找到，分片名称使用运行的时间戳。
• "train"分片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_DatPySci__pythia-1b-kto-iter0", "harness_winogrande_5", split="train")

最新结果

以下是最新结果（来自2024-02-29T15:39:19.717013的运行）： python { "all": { "acc": 0.24774728556136447, "acc_stderr": 0.03041175731725549, "acc_norm": 0.24901099168770932, "acc_norm_stderr": 0.031154173830246844, "mc1": 0.22276621787025705, "mc1_stderr": 0.014566506961396731, "mc2": 0.3640465429999277, "mc2_stderr": 0.014283399348703093 }, "harness|arc:challenge|25": { "acc": 0.2773037542662116, "acc_stderr": 0.013082095839059374, "acc_norm": 0.30119453924914674, "acc_norm_stderr": 0.013406741767847627 }, "harness|hellaswag|10": { "acc": 0.38727345150368453, "acc_stderr": 0.004861314613286841, "acc_norm": 0.48954391555467036, "acc_norm_stderr": 0.00498869022950566 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2518518518518518, "acc_stderr": 0.03749850709174021, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.03749850709174021 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.15789473684210525, "acc_stderr": 0.029674167520101456, "acc_norm": 0.15789473684210525, "acc_norm_stderr": 0.029674167520101456 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.17, "acc_stderr": 0.03775251680686371, "acc_norm": 0.17, "acc_norm_stderr": 0.03775251680686371 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.2641509433962264, "acc_stderr": 0.027134291628741713, "acc_norm": 0.2641509433962264, "acc_norm_stderr": 0.027134291628741713 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.24305555555555555, "acc_stderr": 0.03586879280080341, "acc_norm": 0.24305555555555555, "acc_norm_stderr": 0.03586879280080341 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.19, "acc_stderr": 0.03942772444036623, "acc_norm": 0.19, "acc_norm_stderr": 0.03942772444036623 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.24855491329479767, "acc_stderr": 0.03295304696818318, "acc_norm": 0.24855491329479767, "acc_norm_stderr": 0.03295304696818318 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.24509803921568626, "acc_stderr": 0.042801058373643966, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.042801058373643966 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.251063829787234, "acc_stderr": 0.02834696377716246, "acc_norm": 0.251063829787234, "acc_norm_stderr": 0.02834696377716246 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.21052631578947367, "acc_stderr": 0.038351539543994194, "acc_norm": 0.21052631578947367, "acc_norm_stderr": 0.038351539543994194 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.1793103448275862, "acc_stderr": 0.03196766433373186, "acc_norm": 0.1793103448275862, "acc_norm_stderr": 0.03196766433373186 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.26455026455026454, "acc_stderr": 0.022717467897708617, "acc_norm": 0.26455026455026454, "acc_norm_stderr": 0.022717467897708617 }, "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": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.23870967741935484, "acc_stderr": 0.024251071262208837, "acc_norm": 0.23870967741935484, "acc_norm_stderr": 0.024251071262208837 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2315270935960591, "acc_stderr": 0.02967833314144444, "acc_norm": 0.2315270935960591, "acc_norm_stderr": 0.02967833314144444 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "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": 0.1919191919191919, "acc_stderr": 0.02805779167298901, "acc_norm": 0.1919191919191919, "acc_norm_stderr": 0.02805779167298901 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.24870466321243523, "acc_stderr": 0.03119584087770031, "acc_norm": 0.24870466321243523, "acc_norm_stderr": 0.03119584087770031 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.2153846153846154, "acc_stderr": 0.020843034557462878, "acc_norm": 0.2153846153846154, "acc_norm_stderr": 0.020843034557462878 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2740740740740741, "acc_stderr": 0.027195934804085622, "acc_