five

open-llm-leaderboard/details_yihan6324__llama2-7b-instructmining-orca-40k

收藏
Hugging Face2023-08-27 更新2024-03-04 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard/details_yihan6324__llama2-7b-instructmining-orca-40k
下载链接
链接失效反馈
官方服务:
资源简介:
该数据集是在Open LLM Leaderboard上对模型yihan6324/llama2-7b-instructmining-orca-40k进行评估时自动创建的。它包含61个配置,每个配置对应一个评估任务。数据集包含1次运行的结果,每次运行在每个配置中表示为特定的分割。train分割始终指向最新的结果。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。可以使用提供的Python代码片段加载数据集。
提供机构:
open-llm-leaderboard
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yihan6324/llama2-7b-instructmining-orca-40kOpen LLM Leaderboard上的运行过程中自动创建的。

数据集组成

  • 数据集包含61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,用于计算和显示在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_yihan6324__llama2-7b-instructmining-orca-40k", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是最新结果(来自2023-08-18T00:53:27.654117的运行):

python { "all": { "acc": 0.4847120233306423, "acc_stderr": 0.03527399847085323, "acc_norm": 0.4884455010512822, "acc_norm_stderr": 0.035257414280301984, "mc1": 0.36107711138310894, "mc1_stderr": 0.016814312844836882, "mc2": 0.5103220670450638, "mc2_stderr": 0.015890639542177364 }, "harness|arc:challenge|25": { "acc": 0.5298634812286689, "acc_stderr": 0.014585305840007105, "acc_norm": 0.5674061433447098, "acc_norm_stderr": 0.014478005694182524 }, "harness|hellaswag|10": { "acc": 0.6196972714598685, "acc_stderr": 0.004844690404713595, "acc_norm": 0.8024297948615814, "acc_norm_stderr": 0.0039735233080143454 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750575, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750575 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.48026315789473684, "acc_stderr": 0.040657710025626036, "acc_norm": 0.48026315789473684, "acc_norm_stderr": 0.040657710025626036 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5547169811320755, "acc_stderr": 0.030588052974270655, "acc_norm": 0.5547169811320755, "acc_norm_stderr": 0.030588052974270655 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4583333333333333, "acc_stderr": 0.04166666666666665, "acc_norm": 0.4583333333333333, "acc_norm_stderr": 0.04166666666666665 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.43352601156069365, "acc_stderr": 0.03778621079092055, "acc_norm": 0.43352601156069365, "acc_norm_stderr": 0.03778621079092055 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.27450980392156865, "acc_stderr": 0.044405219061793275, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.044405219061793275 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.40425531914893614, "acc_stderr": 0.03208115750788684, "acc_norm": 0.40425531914893614, "acc_norm_stderr": 0.03208115750788684 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813344, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813344 }, "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": 0.291005291005291, "acc_stderr": 0.023393826500484865, "acc_norm": 0.291005291005291, "acc_norm_stderr": 0.023393826500484865 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.23809523809523808, "acc_stderr": 0.03809523809523811, "acc_norm": 0.23809523809523808, "acc_norm_stderr": 0.03809523809523811 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5645161290322581, "acc_stderr": 0.028206225591502737, "acc_norm": 0.5645161290322581, "acc_norm_stderr": 0.028206225591502737 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.39408866995073893, "acc_stderr": 0.03438157967036543, "acc_norm": 0.39408866995073893, "acc_norm_stderr": 0.03438157967036543 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6121212121212121, "acc_stderr": 0.03804913653971011, "acc_norm": 0.6121212121212121, "acc_norm_stderr": 0.03804913653971011 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6212121212121212, "acc_stderr": 0.03456088731993747, "acc_norm": 0.6212121212121212, "acc_norm_stderr": 0.03456088731993747 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6528497409326425, "acc_stderr": 0.03435696168361355, "acc_norm": 0.6528497409326425, "acc_norm_stderr": 0.03435696168361355 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.46153846153846156, "acc_stderr": 0.025275892070240634, "acc_norm": 0.46153846153846156, "acc_norm_stderr": 0.025275892070240634 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.24814814814814815, "acc_stderr": 0.02633573

5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作