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open-llm-leaderboard-old/details_allknowingroger__LimyQstar-7B-slerp

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Hugging Face2024-04-11 更新2024-06-22 收录
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https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_allknowingroger__LimyQstar-7B-slerp
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资源简介:
该数据集是在模型 allknowingroger/LimyQstar-7B-slerp 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。数据集包含 1 次运行的结果,每次运行在每个配置中作为一个特定的分割,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。文件还提供了如何使用 Python 代码加载运行细节的示例,并列出了特定运行的最新结果。

该数据集是在模型 allknowingroger/LimyQstar-7B-slerp 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。数据集包含 1 次运行的结果,每次运行在每个配置中作为一个特定的分割,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。文件还提供了如何使用 Python 代码加载运行细节的示例,并列出了特定运行的最新结果。
提供机构:
open-llm-leaderboard-old
原始信息汇总

数据集概述

该数据集是在评估模型allknowingroger/LimyQstar-7B-slerpOpen LLM Leaderboard上的自动创建的。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,每个配置对应一个评估任务。
  • 数据来源:数据集从1次运行中创建,每个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。
  • 最新结果:"train"分割总是指向最新的结果。
  • 结果汇总:一个额外的配置"results"存储所有运行的汇总结果,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_allknowingroger__LimyQstar-7B-slerp", "harness_winogrande_5", split="train")

最新结果

以下是2024-04-11T05:02:11.791741运行的最新结果:

python { "all": { "acc": 0.6553765908934429, "acc_stderr": 0.0319556734666647, "acc_norm": 0.656578476600785, "acc_norm_stderr": 0.032604318569600284, "mc1": 0.4479804161566707, "mc1_stderr": 0.017408513063422906, "mc2": 0.6181820821083909, "mc2_stderr": 0.015071153842264392 }, "harness|arc:challenge|25": { "acc": 0.6399317406143344, "acc_stderr": 0.014027516814585186, "acc_norm": 0.6791808873720137, "acc_norm_stderr": 0.013640943091946531 }, "harness|hellaswag|10": { "acc": 0.6800438159729137, "acc_stderr": 0.004655059308602615, "acc_norm": 0.8653654650468035, "acc_norm_stderr": 0.003406352071341722 }, "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": 0.6296296296296297, "acc_stderr": 0.041716541613545426, "acc_norm": 0.6296296296296297, "acc_norm_stderr": 0.041716541613545426 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6907894736842105, "acc_stderr": 0.037610708698674805, "acc_norm": 0.6907894736842105, "acc_norm_stderr": 0.037610708698674805 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.63, "acc_stderr": 0.048523658709391, "acc_norm": 0.63, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7320754716981132, "acc_stderr": 0.027257260322494845, "acc_norm": 0.7320754716981132, "acc_norm_stderr": 0.027257260322494845 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7708333333333334, "acc_stderr": 0.03514697467862388, "acc_norm": 0.7708333333333334, "acc_norm_stderr": 0.03514697467862388 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6878612716763006, "acc_stderr": 0.035331333893236574, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.035331333893236574 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107224, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107224 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.78, "acc_stderr": 0.04163331998932263, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932263 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5914893617021276, "acc_stderr": 0.032134180267015755, "acc_norm": 0.5914893617021276, "acc_norm_stderr": 0.032134180267015755 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4649122807017544, "acc_stderr": 0.04692008381368909, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.04692008381368909 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086924006, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086924006 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4523809523809524, "acc_stderr": 0.044518079590553275, "acc_norm": 0.4523809523809524, "acc_norm_stderr": 0.044518079590553275 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7967741935483871, "acc_stderr": 0.02289168798455496, "acc_norm": 0.7967741935483871, "acc_norm_stderr": 0.02289168798455496 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5270935960591133, "acc_stderr": 0.03512819077876106, "acc_norm": 0.5270935960591133, "acc_norm_stderr": 0.03512819077876106 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.67, "acc_stderr": 0.04725815626252607, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252607 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7757575757575758, "acc_stderr": 0.032568666616811015, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.032568666616811015 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7878787878787878, "acc_stderr": 0.029126522834586818, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.029126522834586818 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8911917098445595, "acc_stderr": 0.022473253332768776, "acc_norm": 0.8911917098445595, "acc_norm_stderr": 0.022473253332768776 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6717948717948717, "acc_stderr": 0.023807633198657266, "acc_norm": 0.6717948717948717, "acc_norm_stderr": 0.023807633198657266 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.35185185185185186, "acc_stderr": 0.02911661760608301, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.

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