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open-llm-leaderboard/details_postitive666__llama3_ruozhiba_8b

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Hugging Face2024-04-19 更新2024-06-12 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard/details_postitive666__llama3_ruozhiba_8b
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资源简介:
该数据集是在模型postitive666/llama3_ruozhiba_8b的评估运行期间自动创建的,评估运行是在Open LLM Leaderboard上进行的。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命名。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,并用于计算和显示Open LLM Leaderboard上的聚合指标。

该数据集是在模型postitive666/llama3_ruozhiba_8b的评估运行期间自动创建的,评估运行是在Open LLM Leaderboard上进行的。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命名。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,并用于计算和显示Open LLM Leaderboard上的聚合指标。
提供机构:
open-llm-leaderboard
原始信息汇总

数据集概述

该数据集是在评估模型 postitive666/llama3_ruozhiba_8bOpen 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

  • 配置数量:63个配置
  • 数据来源:1次运行结果
  • 数据分割:每个配置包含一个特定分割,分割名称使用运行的时间戳。"train" 分割始终指向最新的结果。
  • 额外配置:"results" 配置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_postitive666__llama3_ruozhiba_8b", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-19T18:40:42.337352 运行的最新结果:

python { "all": { "acc": 0.6668689351972811, "acc_stderr": 0.0317882549107606, "acc_norm": 0.6689657873879684, "acc_norm_stderr": 0.03242658324115199, "mc1": 0.3488372093023256, "mc1_stderr": 0.016684419859986893, "mc2": 0.4996694793036768, "mc2_stderr": 0.015277025362254925 }, "harness|arc:challenge|25": { "acc": 0.5742320819112628, "acc_stderr": 0.01444946427886881, "acc_norm": 0.60580204778157, "acc_norm_stderr": 0.014280522667467321 }, "harness|hellaswag|10": { "acc": 0.5932085241983669, "acc_stderr": 0.004902314055725598, "acc_norm": 0.7884883489344752, "acc_norm_stderr": 0.004075456897370668 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6148148148148148, "acc_stderr": 0.042039210401562783, "acc_norm": 0.6148148148148148, "acc_norm_stderr": 0.042039210401562783 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137282, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137282 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.7, "acc_stderr": 0.04605661864718381, "acc_norm": 0.7, "acc_norm_stderr": 0.04605661864718381 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7509433962264151, "acc_stderr": 0.026616482980501704, "acc_norm": 0.7509433962264151, "acc_norm_stderr": 0.026616482980501704 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8055555555555556, "acc_stderr": 0.03309615177059006, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.03309615177059006 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6416184971098265, "acc_stderr": 0.03656343653353159, "acc_norm": 0.6416184971098265, "acc_norm_stderr": 0.03656343653353159 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5, "acc_stderr": 0.04975185951049946, "acc_norm": 0.5, "acc_norm_stderr": 0.04975185951049946 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5872340425531914, "acc_stderr": 0.03218471141400351, "acc_norm": 0.5872340425531914, "acc_norm_stderr": 0.03218471141400351 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.631578947368421, "acc_stderr": 0.04537815354939391, "acc_norm": 0.631578947368421, "acc_norm_stderr": 0.04537815354939391 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6275862068965518, "acc_stderr": 0.04028731532947559, "acc_norm": 0.6275862068965518, "acc_norm_stderr": 0.04028731532947559 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4497354497354497, "acc_stderr": 0.02562085704293665, "acc_norm": 0.4497354497354497, "acc_norm_stderr": 0.02562085704293665 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.48412698412698413, "acc_stderr": 0.04469881854072606, "acc_norm": 0.48412698412698413, "acc_norm_stderr": 0.04469881854072606 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7774193548387097, "acc_stderr": 0.023664216671642507, "acc_norm": 0.7774193548387097, "acc_norm_stderr": 0.023664216671642507 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4975369458128079, "acc_stderr": 0.03517945038691063, "acc_norm": 0.4975369458128079, "acc_norm_stderr": 0.03517945038691063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.76, "acc_stderr": 0.04292346959909282, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909282 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8383838383838383, "acc_stderr": 0.02622591986362927, "acc_norm": 0.8383838383838383, "acc_norm_stderr": 0.02622591986362927 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9119170984455959, "acc_stderr": 0.02045374660160103, "acc_norm": 0.9119170984455959, "acc_norm_stderr": 0.02045374660160103 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6717948717948717, "acc_stderr": 0.02380763319865726, "acc_norm": 0.6717948717948717, "acc_norm_stderr": 0.02380763319865726 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.37407407407407406, "acc_stderr": 0.029502861128955286, "acc_norm": 0.37407407407407406, "acc_norm_stderr": 0.029502861128955286 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0

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