open-llm-leaderboard-old/details_Qwen__Qwen1.5-1.8B-Chat

该数据集是在Open LLM Leaderboard上对模型Qwen/Qwen1.5-1.8B-Chat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次运行中生成的，每次运行在每个配置中表示为特定的拆分，train拆分始终指向最新结果。一个名为results的额外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。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

数据集名称

Evaluation run of Qwen/Qwen1.5-1.8B-Chat

数据集摘要

该数据集是在模型 Qwen/Qwen1.5-1.8B-Chat 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_Qwen__Qwen1.5-1.8B-Chat", "harness_winogrande_5", split="train")

最新结果

这些是最新结果（来自 2024-03-04T13:07:02.137587 运行）的示例： python { "all": { "acc": 0.45508603114975144, "acc_stderr": 0.034539651859713145, "acc_norm": 0.45985536481060507, "acc_norm_stderr": 0.03529464074646668, "mc1": 0.26438188494492043, "mc1_stderr": 0.015438211119522512, "mc2": 0.406175277448171, "mc2_stderr": 0.01480381400694316 }, "harness|arc:challenge|25": { "acc": 0.36689419795221845, "acc_stderr": 0.014084133118104289, "acc_norm": 0.3873720136518771, "acc_norm_stderr": 0.01423587248790987 }, "harness|hellaswag|10": { "acc": 0.46245767775343555, "acc_stderr": 0.004975696076240845, "acc_norm": 0.60017924716192, "acc_norm_stderr": 0.004888601874547487 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.37777777777777777, "acc_stderr": 0.04188307537595853, "acc_norm": 0.37777777777777777, "acc_norm_stderr": 0.04188307537595853 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5197368421052632, "acc_stderr": 0.04065771002562603, "acc_norm": 0.5197368421052632, "acc_norm_stderr": 0.04065771002562603 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4981132075471698, "acc_stderr": 0.030772653642075664, "acc_norm": 0.4981132075471698, "acc_norm_stderr": 0.030772653642075664 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04155319955593146, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04155319955593146 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.22, "acc_stderr": 0.041633319989322695, "acc_norm": 0.22, "acc_norm_stderr": 0.041633319989322695 }, "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": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.42196531791907516, "acc_stderr": 0.037657466938651504, "acc_norm": 0.42196531791907516, "acc_norm_stderr": 0.037657466938651504 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.28431372549019607, "acc_stderr": 0.04488482852329017, "acc_norm": 0.28431372549019607, "acc_norm_stderr": 0.04488482852329017 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.39148936170212767, "acc_stderr": 0.031907012423268113, "acc_norm": 0.39148936170212767, "acc_norm_stderr": 0.031907012423268113 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2807017543859649, "acc_stderr": 0.042270544512322, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.042270544512322 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4206896551724138, "acc_stderr": 0.0411391498118926, "acc_norm": 0.4206896551724138, "acc_norm_stderr": 0.0411391498118926 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.35978835978835977, "acc_stderr": 0.024718075944129277, "acc_norm": 0.35978835978835977, "acc_norm_stderr": 0.024718075944129277 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.24603174603174602, "acc_stderr": 0.03852273364924315, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.03852273364924315 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5161290322580645, "acc_stderr": 0.028429203176724555, "acc_norm": 0.5161290322580645, "acc_norm_stderr": 0.028429203176724555 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.32019704433497537, "acc_stderr": 0.032826493853041504, "acc_norm": 0.32019704433497537, "acc_norm_stderr": 0.032826493853041504 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6181818181818182, "acc_stderr": 0.03793713171165635, "acc_norm": 0.6181818181818182, "acc_norm_stderr": 0.03793713171165635 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5909090909090909, "acc_stderr": 0.03502975799413007, "acc_norm": 0.5909090909090909, "acc_norm_stderr": 0.03502975799413007 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5699481865284974, "acc_stderr": 0.03572954333144808, "acc_norm": 0.5699481865284974, "acc_norm_stderr": 0.03572954333144808 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.3641025641025641, "acc_stderr": 0.024396672985094757, "acc_norm": 0.3641025641025641, "acc_norm_stderr": 0.024396672985094757 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3111111111111111, "acc_stderr": 0.028226446749683515, "acc_norm": 0.3111111111111111, "acc_norm_stderr": 0.028226446749683515