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open-llm-leaderboard-old/details_BioMistral__BioMistral-7B-TIES

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Hugging Face2024-02-18 更新2024-06-22 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_BioMistral__BioMistral-7B-TIES
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资源简介:
该数据集是在Open LLM Leaderboard上对BioMistral/BioMistral-7B-TIES模型进行评估时自动创建的。数据集由63个配置组成,每个配置对应一个被评估的任务。数据集是从一个或多个运行中生成的,每个运行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,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BioMistral/BioMistral-7B-TIES模型进行评估时自动创建的。数据集由63个配置组成,每个配置对应一个被评估的任务。数据集是从一个或多个运行中生成的,每个运行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,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

该数据集是在对模型 BioMistral/BioMistral-7B-TIES 进行评估运行期间自动创建的,用于 Open LLM Leaderboard

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_BioMistral__BioMistral-7B-TIES", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-18T15:11:02.781867 运行的最新结果

python { "all": { "acc": 0.5564946111491779, "acc_stderr": 0.03367365623879565, "acc_norm": 0.5667186655272123, "acc_norm_stderr": 0.034567311758120334, "mc1": 0.3561811505507956, "mc1_stderr": 0.016763790728446342, "mc2": 0.5220069897600659, "mc2_stderr": 0.015374877041453508 }, "harness|arc:challenge|25": { "acc": 0.5179180887372014, "acc_stderr": 0.014602005585490978, "acc_norm": 0.5546075085324232, "acc_norm_stderr": 0.014523987638344085 }, "harness|hellaswag|10": { "acc": 0.602867954590719, "acc_stderr": 0.004883037758919962, "acc_norm": 0.795857398924517, "acc_norm_stderr": 0.004022499210760733 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5592105263157895, "acc_stderr": 0.04040311062490436, "acc_norm": 0.5592105263157895, "acc_norm_stderr": 0.04040311062490436 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6528301886792452, "acc_stderr": 0.029300101705549645, "acc_norm": 0.6528301886792452, "acc_norm_stderr": 0.029300101705549645 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6041666666666666, "acc_stderr": 0.04089465449325582, "acc_norm": 0.6041666666666666, "acc_norm_stderr": 0.04089465449325582 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5895953757225434, "acc_stderr": 0.03750757044895537, "acc_norm": 0.5895953757225434, "acc_norm_stderr": 0.03750757044895537 }, "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": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4808510638297872, "acc_stderr": 0.032662042990646775, "acc_norm": 0.4808510638297872, "acc_norm_stderr": 0.032662042990646775 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.35964912280701755, "acc_stderr": 0.045144961328736334, "acc_norm": 0.35964912280701755, "acc_norm_stderr": 0.045144961328736334 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4689655172413793, "acc_stderr": 0.04158632762097828, "acc_norm": 0.4689655172413793, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.37037037037037035, "acc_stderr": 0.02487081525105709, "acc_norm": 0.37037037037037035, "acc_norm_stderr": 0.02487081525105709 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.373015873015873, "acc_stderr": 0.04325506042017086, "acc_norm": 0.373015873015873, "acc_norm_stderr": 0.04325506042017086 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6870967741935484, "acc_stderr": 0.02637756702864586, "acc_norm": 0.6870967741935484, "acc_norm_stderr": 0.02637756702864586 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.43842364532019706, "acc_stderr": 0.03491207857486519, "acc_norm": 0.43842364532019706, "acc_norm_stderr": 0.03491207857486519 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6787878787878788, "acc_stderr": 0.03646204963253812, "acc_norm": 0.6787878787878788, "acc_norm_stderr": 0.03646204963253812 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6919191919191919, "acc_stderr": 0.032894773300986155, "acc_norm": 0.6919191919191919, "acc_norm_stderr": 0.032894773300986155 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8031088082901554, "acc_stderr": 0.02869787397186067, "acc_norm": 0.8031088082901554, "acc_norm_stderr": 0.02869787397186067 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5538461538461539, "acc_stderr": 0.025203571773028333, "acc_norm": 0.5538461538461539, "acc_norm_stderr": 0.025203571773028333 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.337037037037037, "acc_stderr": 0.02882088466625326, "acc_norm": 0.337037037037037, "acc_norm_stderr": 0.

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