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open-llm-leaderboard-old/details_macadeliccc__SOLAR-10.7b-Instruct-truthy-dpo

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Hugging Face2024-02-01 更新2024-06-22 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_macadeliccc__SOLAR-10.7b-Instruct-truthy-dpo
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资源简介:
该数据集是在评估模型macadeliccc/SOLAR-10.7b-Instruct-truthy-dpo时自动创建的,评估在Open LLM Leaderboard上进行。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。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。

该数据集是在评估模型macadeliccc/SOLAR-10.7b-Instruct-truthy-dpo时自动创建的,评估在Open LLM Leaderboard上进行。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。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-old
原始信息汇总

数据集概述

数据集摘要

该数据集是在评估模型 macadeliccc/SOLAR-10.7b-Instruct-truthy-dpoOpen LLM Leaderboard 上的自动创建的。

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。
  • "train" 分割总是指向最新的结果。
  • 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_macadeliccc__SOLAR-10.7b-Instruct-truthy-dpo", "harness_winogrande_5", split="train")

最新结果

这些是最新结果的示例: python { "all": { "acc": 0.6578797312429587, "acc_stderr": 0.03193533127801232, "acc_norm": 0.6595146193672972, "acc_norm_stderr": 0.03257985736954445, "mc1": 0.6046511627906976, "mc1_stderr": 0.017115815632418208, "mc2": 0.7675318116403941, "mc2_stderr": 0.01417571671037387 }, "harness|arc:challenge|25": { "acc": 0.6953924914675768, "acc_stderr": 0.013449522109932487, "acc_norm": 0.7209897610921502, "acc_norm_stderr": 0.01310678488360134 }, "harness|hellaswag|10": { "acc": 0.710017924716192, "acc_stderr": 0.004528264116475881, "acc_norm": 0.8843855805616411, "acc_norm_stderr": 0.003191084792793155 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6, "acc_stderr": 0.04232073695151589, "acc_norm": 0.6, "acc_norm_stderr": 0.04232073695151589 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.743421052631579, "acc_stderr": 0.0355418036802569, "acc_norm": 0.743421052631579, "acc_norm_stderr": 0.0355418036802569 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.76, "acc_stderr": 0.04292346959909282, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909282 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6679245283018868, "acc_stderr": 0.02898545565233439, "acc_norm": 0.6679245283018868, "acc_norm_stderr": 0.02898545565233439 }, "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": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.35294117647058826, "acc_stderr": 0.04755129616062946, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.04755129616062946 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768077, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768077 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6127659574468085, "acc_stderr": 0.03184389265339526, "acc_norm": 0.6127659574468085, "acc_norm_stderr": 0.03184389265339526 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.04702880432049615, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.04702880432049615 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6068965517241379, "acc_stderr": 0.040703290137070705, "acc_norm": 0.6068965517241379, "acc_norm_stderr": 0.040703290137070705 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.48412698412698413, "acc_stderr": 0.025738330639412152, "acc_norm": 0.48412698412698413, "acc_norm_stderr": 0.025738330639412152 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4365079365079365, "acc_stderr": 0.04435932892851466, "acc_norm": 0.4365079365079365, "acc_norm_stderr": 0.04435932892851466 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8032258064516129, "acc_stderr": 0.022616409420742025, "acc_norm": 0.8032258064516129, "acc_norm_stderr": 0.022616409420742025 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4975369458128079, "acc_stderr": 0.035179450386910616, "acc_norm": 0.4975369458128079, "acc_norm_stderr": 0.035179450386910616 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.793939393939394, "acc_stderr": 0.03158415324047711, "acc_norm": 0.793939393939394, "acc_norm_stderr": 0.03158415324047711 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8484848484848485, "acc_stderr": 0.025545650426603627, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.025545650426603627 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8860103626943006, "acc_stderr": 0.02293514405391943, "acc_norm": 0.8860103626943006, "acc_norm_stderr": 0.02293514405391943 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6641025641025641, "acc_stderr": 0.023946724741563976, "acc_norm": 0.6641025641025641, "acc_norm_stderr": 0.023946724741563976 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.36666666666666664, "acc_stderr": 0.029381620726465073, "acc_norm": 0.36666666666666664, "acc_norm_stderr": 0.029381620726465073 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.680672268907563, "acc_stderr": 0.0302839955258844, "acc_norm": 0.6

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