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open-llm-leaderboard-old/details_NovoCode__Mistral-NeuralDPO-v0.3

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Hugging Face2024-02-19 更新2024-06-22 收录
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https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_NovoCode__Mistral-NeuralDPO-v0.3
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资源简介:
该数据集是在模型NovoCode/Mistral-NeuralDPO-v0.3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。它包含1次运行的数据,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。

该数据集是在模型NovoCode/Mistral-NeuralDPO-v0.3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。它包含1次运行的数据,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。
提供机构:
open-llm-leaderboard-old
原始信息汇总

数据集概述

数据集摘要

该数据集是在模型NovoCode/Mistral-NeuralDPO-v0.3Open LLM Leaderboard上的评估运行期间自动创建的。

数据集组成

  • 该数据集包含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。
  • 额外的"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_NovoCode__Mistral-NeuralDPO-v0.3", "harness_winogrande_5", split="train")

最新结果

这些是最新的结果,来自2024-02-19T10:09:09.378755的运行: python { "all": { "acc": 0.6136008844819947, "acc_stderr": 0.03271584502877658, "acc_norm": 0.61963655051764, "acc_norm_stderr": 0.03338202033480734, "mc1": 0.29498164014687883, "mc1_stderr": 0.01596440096558966, "mc2": 0.4531069456128054, "mc2_stderr": 0.01430354313553265 }, "harness|arc:challenge|25": { "acc": 0.5750853242320819, "acc_stderr": 0.014445698968520769, "acc_norm": 0.6160409556313993, "acc_norm_stderr": 0.014212444980651892 }, "harness|hellaswag|10": { "acc": 0.6150169288986258, "acc_stderr": 0.004855968578998724, "acc_norm": 0.8315076677952599, "acc_norm_stderr": 0.003735379375255013 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5925925925925926, "acc_stderr": 0.04244633238353228, "acc_norm": 0.5925925925925926, "acc_norm_stderr": 0.04244633238353228 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6513157894736842, "acc_stderr": 0.0387813988879761, "acc_norm": 0.6513157894736842, "acc_norm_stderr": 0.0387813988879761 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6679245283018868, "acc_stderr": 0.028985455652334395, "acc_norm": 0.6679245283018868, "acc_norm_stderr": 0.028985455652334395 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7083333333333334, "acc_stderr": 0.038009680605548594, "acc_norm": 0.7083333333333334, "acc_norm_stderr": 0.038009680605548594 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6127167630057804, "acc_stderr": 0.037143259063020656, "acc_norm": 0.6127167630057804, "acc_norm_stderr": 0.037143259063020656 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.35294117647058826, "acc_stderr": 0.047551296160629454, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.047551296160629454 }, "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": 0.5404255319148936, "acc_stderr": 0.03257901482099835, "acc_norm": 0.5404255319148936, "acc_norm_stderr": 0.03257901482099835 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.45614035087719296, "acc_stderr": 0.04685473041907789, "acc_norm": 0.45614035087719296, "acc_norm_stderr": 0.04685473041907789 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5724137931034483, "acc_stderr": 0.041227371113703316, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.041227371113703316 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3941798941798942, "acc_stderr": 0.02516798233389414, "acc_norm": 0.3941798941798942, "acc_norm_stderr": 0.02516798233389414 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3412698412698413, "acc_stderr": 0.04240799327574925, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.04240799327574925 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7516129032258064, "acc_stderr": 0.024580028921481006, "acc_norm": 0.7516129032258064, "acc_norm_stderr": 0.024580028921481006 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4876847290640394, "acc_stderr": 0.035169204442208966, "acc_norm": 0.4876847290640394, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7636363636363637, "acc_stderr": 0.03317505930009182, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.03317505930009182 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7626262626262627, "acc_stderr": 0.0303137105381989, "acc_norm": 0.7626262626262627, "acc_norm_stderr": 0.0303137105381989 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8393782383419689, "acc_stderr": 0.026499057701397457, "acc_norm": 0.8393782383419689, "acc_norm_stderr": 0.026499057701397457 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.617948717948718, "acc_stderr": 0.024635549163908234, "acc_norm": 0.617948717948718, "acc_norm_stderr": 0.024635549163908234 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3296296296296296, "acc_stderr": 0.028661201116524575, "acc_norm": 0.3296296296296296, "acc_norm_stderr": 0.028661201116524575 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6218487394957983, "

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