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open-llm-leaderboard-old/details_ziniuli__Mistral-7B-ReMax-v0.1

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Hugging Face2024-03-11 更新2024-06-22 收录
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https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_ziniuli__Mistral-7B-ReMax-v0.1
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资源简介:
该数据集是在模型 ziniuli/Mistral-7B-ReMax-v0.1 在 Open LLM Leaderboard 上进行评估时自动生成的。数据集包含 63 个配置,每个配置对应一个评估任务。数据集由 2 次运行的数据组成,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。此外,还有一个名为 results 的配置,用于存储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 文件还提供了如何使用 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。

该数据集是在模型 ziniuli/Mistral-7B-ReMax-v0.1 在 Open LLM Leaderboard 上进行评估时自动生成的。数据集包含 63 个配置,每个配置对应一个评估任务。数据集由 2 次运行的数据组成,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。此外,还有一个名为 results 的配置,用于存储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 文件还提供了如何使用 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

数据集简介

该数据集是在评估模型ziniuli/Mistral-7B-ReMax-v0.1Open LLM Leaderboard上的自动创建的。

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。
  • 运行次数:数据集从2次运行中创建。每次运行在每个配置中作为一个特定的分割存在,分割名称使用运行的时间戳。
  • 训练分割:"train"分割始终指向最新的结果。
  • 结果配置: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_ziniuli__Mistral-7B-ReMax-v0.1", "harness_winogrande_5", split="train")

最新结果

这些是最新的结果,来自2024-03-11T18:07:55.437908的运行: python { "all": { "acc": 0.6076779028291911, "acc_stderr": 0.03315115503196382, "acc_norm": 0.61214149482687, "acc_norm_stderr": 0.03382378734979988, "mc1": 0.5287637698898409, "mc1_stderr": 0.017474513848525518, "mc2": 0.6815516476213737, "mc2_stderr": 0.015177768821414346 }, "harness|arc:challenge|25": { "acc": 0.5964163822525598, "acc_stderr": 0.014337158914268445, "acc_norm": 0.6331058020477816, "acc_norm_stderr": 0.014084133118104301 }, "harness|hellaswag|10": { "acc": 0.6692889862577176, "acc_stderr": 0.004695076629884538, "acc_norm": 0.8498307110137423, "acc_norm_stderr": 0.0035650718701954473 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5703703703703704, "acc_stderr": 0.042763494943765995, "acc_norm": 0.5703703703703704, "acc_norm_stderr": 0.042763494943765995 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6118421052631579, "acc_stderr": 0.03965842097512744, "acc_norm": 0.6118421052631579, "acc_norm_stderr": 0.03965842097512744 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6754716981132075, "acc_stderr": 0.02881561571343211, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.02881561571343211 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6875, "acc_stderr": 0.038760854559127644, "acc_norm": 0.6875, "acc_norm_stderr": 0.038760854559127644 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5953757225433526, "acc_stderr": 0.03742461193887248, "acc_norm": 0.5953757225433526, "acc_norm_stderr": 0.03742461193887248 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4215686274509804, "acc_stderr": 0.04913595201274498, "acc_norm": 0.4215686274509804, "acc_norm_stderr": 0.04913595201274498 }, "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": 0.5361702127659574, "acc_stderr": 0.032600385118357715, "acc_norm": 0.5361702127659574, "acc_norm_stderr": 0.032600385118357715 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.41228070175438597, "acc_stderr": 0.046306532033665956, "acc_norm": 0.41228070175438597, "acc_norm_stderr": 0.046306532033665956 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6137931034482759, "acc_stderr": 0.04057324734419035, "acc_norm": 0.6137931034482759, "acc_norm_stderr": 0.04057324734419035 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.38095238095238093, "acc_stderr": 0.025010749116137602, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.025010749116137602 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4126984126984127, "acc_stderr": 0.04403438954768176, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.04403438954768176 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6516129032258065, "acc_stderr": 0.02710482632810094, "acc_norm": 0.6516129032258065, "acc_norm_stderr": 0.02710482632810094 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5073891625615764, "acc_stderr": 0.0351760354036101, "acc_norm": 0.5073891625615764, "acc_norm_stderr": 0.0351760354036101 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7393939393939394, "acc_stderr": 0.034277431758165236, "acc_norm": 0.7393939393939394, "acc_norm_stderr": 0.034277431758165236 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7626262626262627, "acc_stderr": 0.030313710538198896, "acc_norm": 0.7626262626262627, "acc_norm_stderr": 0.030313710538198896 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8497409326424871, "acc_stderr": 0.02578772318072387, "acc_norm": 0.8497409326424871, "acc_norm_stderr": 0.02578772318072387 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.558974358974359, "acc_stderr": 0.025174048384000745, "acc_norm": 0.558974358974359, "acc_norm_stderr": 0.025174048384000745 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3111111111111111, "acc_stderr": 0.02822644674968351, "acc_norm": 0.3111111111111111, "acc_norm_stderr": 0.02822644674968351 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6470588235294118, "acc_stderr": 0

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