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open-llm-leaderboard-old/details_jingyeom__freeze_KoSoLAR-10.7B-v0.2_1.4_dedup

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Hugging Face2024-02-09 更新2024-06-22 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard-old/details_jingyeom__freeze_KoSoLAR-10.7B-v0.2_1.4_dedup
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资源简介:
该数据集是在模型[jingyeom/freeze_KoSoLAR-10.7B-v0.2_1.4_dedup]的评估运行中自动创建的。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1次运行中创建的,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,一个名为results的配置存储了所有运行的聚合结果,并用于计算和显示在Open LLM Leaderboard上的聚合指标。

该数据集是在模型[jingyeom/freeze_KoSoLAR-10.7B-v0.2_1.4_dedup]的评估运行中自动创建的。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1次运行中创建的,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,一个名为results的配置存储了所有运行的聚合结果,并用于计算和显示在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

该数据集是在对模型 jingyeom/freeze_KoSoLAR-10.7B-v0.2_1.4_dedup 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,每次运行可以在每个配置中找到特定的拆分,拆分名称使用运行的时间戳。
  • 每个配置中的 "train" 拆分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 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_jingyeom__freeze_KoSoLAR-10.7B-v0.2_1.4_dedup", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-09T19:47:27.132798 运行的最新结果

python { "all": { "acc": 0.6427828139999391, "acc_stderr": 0.03180043003386348, "acc_norm": 0.6500272402365154, "acc_norm_stderr": 0.03244696674206044, "mc1": 0.3047735618115055, "mc1_stderr": 0.016114124156882455, "mc2": 0.4449971855988083, "mc2_stderr": 0.01491170317496814 }, "harness|arc:challenge|25": { "acc": 0.5426621160409556, "acc_stderr": 0.01455810654392406, "acc_norm": 0.5844709897610921, "acc_norm_stderr": 0.01440136664121639 }, "harness|hellaswag|10": { "acc": 0.5994821748655647, "acc_stderr": 0.0048900193560210865, "acc_norm": 0.8125871340370444, "acc_norm_stderr": 0.0038944505016930368 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.26, "acc_stderr": 0.04408440022768081, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768081 }, "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": 0.7236842105263158, "acc_stderr": 0.03639057569952929, "acc_norm": 0.7236842105263158, "acc_norm_stderr": 0.03639057569952929 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7094339622641509, "acc_stderr": 0.027943219989337142, "acc_norm": 0.7094339622641509, "acc_norm_stderr": 0.027943219989337142 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7569444444444444, "acc_stderr": 0.0358687928008034, "acc_norm": 0.7569444444444444, "acc_norm_stderr": 0.0358687928008034 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "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": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "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": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5829787234042553, "acc_stderr": 0.03223276266711712, "acc_norm": 0.5829787234042553, "acc_norm_stderr": 0.03223276266711712 }, "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": 0.6, "acc_stderr": 0.040824829046386284, "acc_norm": 0.6, "acc_norm_stderr": 0.040824829046386284 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4576719576719577, "acc_stderr": 0.025658868862058336, "acc_norm": 0.4576719576719577, "acc_norm_stderr": 0.025658868862058336 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7806451612903226, "acc_stderr": 0.02354079935872329, "acc_norm": 0.7806451612903226, "acc_norm_stderr": 0.02354079935872329 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.49261083743842365, "acc_stderr": 0.035176035403610084, "acc_norm": 0.49261083743842365, "acc_norm_stderr": 0.035176035403610084 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.793939393939394, "acc_stderr": 0.0315841532404771, "acc_norm": 0.793939393939394, "acc_norm_stderr": 0.0315841532404771 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8383838383838383, "acc_stderr": 0.026225919863629283, "acc_norm": 0.8383838383838383, "acc_norm_stderr": 0.026225919863629283 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9067357512953368, "acc_stderr": 0.02098685459328973, "acc_norm": 0.9067357512953368, "acc_norm_stderr": 0.02098685459328973 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6410256410256411, "acc_stderr": 0.024321738484602354, "acc_norm": 0.6410256410256411, "acc_norm_stderr": 0.024321738484602354 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.35185185185185186, "acc_stderr": 0.029116617606083025, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.029116617606083025 }, "harness|

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