open-llm-leaderboard-old/details_liminerity__mm4-3b

该数据集是在模型liminerity/mm4-3b的评估运行期间自动创建的，用于Open LLM Leaderboard。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1次运行创建，每次运行可以在每个配置中找到，分割名称使用运行的时间戳。train分割始终指向最新结果。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。

原始信息汇总

数据集概述

该数据集是在对模型 liminerity/mm4-3b 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作为一个特定的分割找到，分割名称使用运行的时间戳。
• "train" 分割始终指向最新的结果。
• 额外的 "results" 配置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_liminerity__mm4-3b", "harness_winogrande_5", split="train")

最新结果

以下是 最新结果 的摘要：

python { "all": { "acc": 0.5089370141170166, "acc_stderr": 0.034495031887601606, "acc_norm": 0.5112482639267588, "acc_norm_stderr": 0.035202963761089084, "mc1": 0.2741738066095471, "mc1_stderr": 0.015616518497219373, "mc2": 0.4319914152632235, "mc2_stderr": 0.014565062766855538 }, "harness|arc:challenge|25": { "acc": 0.4087030716723549, "acc_stderr": 0.014365750345427005, "acc_norm": 0.44795221843003413, "acc_norm_stderr": 0.01453201149821167 }, "harness|hellaswag|10": { "acc": 0.5244971121290579, "acc_stderr": 0.004983788992681208, "acc_norm": 0.704142601075483, "acc_norm_stderr": 0.0045549440206205 }, "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": 0.4074074074074074, "acc_stderr": 0.042446332383532286, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.042446332383532286 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5394736842105263, "acc_stderr": 0.04056242252249034, "acc_norm": 0.5394736842105263, "acc_norm_stderr": 0.04056242252249034 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.56, "acc_stderr": 0.049888765156985884, "acc_norm": 0.56, "acc_norm_stderr": 0.049888765156985884 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5547169811320755, "acc_stderr": 0.030588052974270655, "acc_norm": 0.5547169811320755, "acc_norm_stderr": 0.030588052974270655 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5694444444444444, "acc_stderr": 0.04140685639111502, "acc_norm": 0.5694444444444444, "acc_norm_stderr": 0.04140685639111502 }, "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": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5260115606936416, "acc_stderr": 0.03807301726504513, "acc_norm": 0.5260115606936416, "acc_norm_stderr": 0.03807301726504513 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4, "acc_stderr": 0.03202563076101735, "acc_norm": 0.4, "acc_norm_stderr": 0.03202563076101735 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3508771929824561, "acc_stderr": 0.04489539350270699, "acc_norm": 0.3508771929824561, "acc_norm_stderr": 0.04489539350270699 }, "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": 0.35185185185185186, "acc_stderr": 0.024594975128920945, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.024594975128920945 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.31746031746031744, "acc_stderr": 0.04163453031302859, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.04163453031302859 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6225806451612903, "acc_stderr": 0.027575960723278243, "acc_norm": 0.6225806451612903, "acc_norm_stderr": 0.027575960723278243 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.39408866995073893, "acc_stderr": 0.03438157967036545, "acc_norm": 0.39408866995073893, "acc_norm_stderr": 0.03438157967036545 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5393939393939394, "acc_stderr": 0.03892207016552012, "acc_norm": 0.5393939393939394, "acc_norm_stderr": 0.03892207016552012 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6464646464646465, "acc_stderr": 0.03406086723547155, "acc_norm": 0.6464646464646465, "acc_norm_stderr": 0.03406086723547155 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.694300518134715, "acc_stderr": 0.033248379397581594, "acc_norm": 0.694300518134715, "acc_norm_stderr": 0.033248379397581594 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4794871794871795, "acc_stderr": 0.025329663163489943, "acc_norm": 0.4794871794871795, "acc_norm_stderr": 0.025329663163489943 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2518518518518518, "acc_stderr": 0.026466117538959916, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.026466117538959916 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.542016806