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open-llm-leaderboard-old/details_viethq188__Rabbit-7B-DPO-Chat

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Hugging Face2023-12-12 更新2024-06-22 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_viethq188__Rabbit-7B-DPO-Chat
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资源简介:
该数据集是在Open LLM Leaderboard上对模型viethq188/Rabbit-7B-DPO-Chat进行评估时自动创建的。数据集由63个配置组成,每个配置对应一个评估任务。数据集包含一次运行的结果,每次运行都作为每个配置中的一个特定分割存储。train分割始终指向最新结果。此外,还有一个results配置,用于存储所有运行的聚合结果,并用于在Open LLM Leaderboard上计算和显示聚合指标。README还提供了如何使用Hugging Face datasets库加载数据集的示例,并包含了特定运行的最新结果。

该数据集是在Open LLM Leaderboard上对模型viethq188/Rabbit-7B-DPO-Chat进行评估时自动创建的。数据集由63个配置组成,每个配置对应一个评估任务。数据集包含一次运行的结果,每次运行都作为每个配置中的一个特定分割存储。train分割始终指向最新结果。此外,还有一个results配置,用于存储所有运行的聚合结果,并用于在Open LLM Leaderboard上计算和显示聚合指标。README还提供了如何使用Hugging Face datasets库加载数据集的示例,并包含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

数据集摘要

该数据集是在对模型 viethq188/Rabbit-7B-DPO-Chat 进行评估运行期间自动创建的,评估结果显示在 Open LLM Leaderboard 上。

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,每个运行在每个配置中作为一个特定的分片存在,分片名称使用运行的时间戳。
  • “train” 分片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_viethq188__Rabbit-7B-DPO-Chat", "harness_winogrande_5", split="train")

最新结果

以下是 2023-12-12T12:42:05.129692 运行的最新结果

python { "all": { "acc": 0.6100718716052655, "acc_stderr": 0.03311439179911609, "acc_norm": 0.6112562424256339, "acc_norm_stderr": 0.03378279812081705, "mc1": 0.48959608323133413, "mc1_stderr": 0.017499711430249264, "mc2": 0.6217820822805159, "mc2_stderr": 0.015655139839426707 }, "harness|arc:challenge|25": { "acc": 0.6578498293515358, "acc_stderr": 0.013864152159177275, "acc_norm": 0.7030716723549488, "acc_norm_stderr": 0.013352025976725227 }, "harness|hellaswag|10": { "acc": 0.6928898625771759, "acc_stderr": 0.004603527017557839, "acc_norm": 0.8743278231428002, "acc_norm_stderr": 0.0033080208244267903 }, "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": 0.5407407407407407, "acc_stderr": 0.04304979692464241, "acc_norm": 0.5407407407407407, "acc_norm_stderr": 0.04304979692464241 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6381578947368421, "acc_stderr": 0.03910525752849724, "acc_norm": 0.6381578947368421, "acc_norm_stderr": 0.03910525752849724 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.660377358490566, "acc_stderr": 0.02914690474779833, "acc_norm": 0.660377358490566, "acc_norm_stderr": 0.02914690474779833 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6736111111111112, "acc_stderr": 0.03921067198982266, "acc_norm": 0.6736111111111112, "acc_norm_stderr": 0.03921067198982266 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6242774566473989, "acc_stderr": 0.03692820767264866, "acc_norm": 0.6242774566473989, "acc_norm_stderr": 0.03692820767264866 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.37254901960784315, "acc_stderr": 0.04810840148082636, "acc_norm": 0.37254901960784315, "acc_norm_stderr": 0.04810840148082636 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5148936170212766, "acc_stderr": 0.03267151848924777, "acc_norm": 0.5148936170212766, "acc_norm_stderr": 0.03267151848924777 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5379310344827586, "acc_stderr": 0.04154659671707548, "acc_norm": 0.5379310344827586, "acc_norm_stderr": 0.04154659671707548 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086923996, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086923996 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7290322580645161, "acc_stderr": 0.025284416114900152, "acc_norm": 0.7290322580645161, "acc_norm_stderr": 0.025284416114900152 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.47783251231527096, "acc_stderr": 0.03514528562175008, "acc_norm": 0.47783251231527096, "acc_norm_stderr": 0.03514528562175008 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.703030303030303, "acc_stderr": 0.0356796977226805, "acc_norm": 0.703030303030303, "acc_norm_stderr": 0.0356796977226805 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7727272727272727, "acc_stderr": 0.029857515673386417, "acc_norm": 0.7727272727272727, "acc_norm_stderr": 0.029857515673386417 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8549222797927462, "acc_stderr": 0.025416343096306405, "acc_norm": 0.8549222797927462, "acc_norm_stderr": 0.025416343096306405 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6230769230769231, "acc_stderr": 0.024570975364225995, "acc_norm": 0.6230769230769231, "acc_norm_stderr": 0.024570975364225995 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34444444444444444, "acc_stderr": 0.02897264888484427, "

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