open-llm-leaderboard-old/details_aboros98__merlin1.4

该数据集是在Open LLM Leaderboard上对模型`aboros98/merlin1.4`进行评估运行时自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。数据集是从1次运行中创建的，每次运行的结果可以在每个配置的特定分割中找到，分割名称使用运行的时间戳。train分割始终指向最新的结果。此外，还有一个名为results的配置存储了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。

原始信息汇总

数据集概述

数据集简介

该数据集是在对模型 aboros98/merlin1.4 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

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。
• 数据来源：数据集从1次运行中创建，每个运行结果作为一个特定的分割（split）存储，分割名称使用运行的时间戳。
• 最新结果："train" 分割始终指向最新的结果。
• 聚合结果：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_aboros98__merlin1.4", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-15T12:59:35.847418 运行的最新结果：

python { "all": { "acc": 0.5651825045623053, "acc_stderr": 0.03399328820379374, "acc_norm": 0.5670113817407626, "acc_norm_stderr": 0.03469345112171627, "mc1": 0.32558139534883723, "mc1_stderr": 0.016403989469907825, "mc2": 0.4735785703076855, "mc2_stderr": 0.015147123054621936 }, "harness|arc:challenge|25": { "acc": 0.5631399317406144, "acc_stderr": 0.014494421584256519, "acc_norm": 0.5930034129692833, "acc_norm_stderr": 0.014356399418009123 }, "harness|hellaswag|10": { "acc": 0.5630352519418442, "acc_stderr": 0.004949969363017659, "acc_norm": 0.7449711212905795, "acc_norm_stderr": 0.004349866376068982 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.04461960433384741, "acc_norm": 0.27, "acc_norm_stderr": 0.04461960433384741 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04292596718256981, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04292596718256981 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5723684210526315, "acc_stderr": 0.04026097083296563, "acc_norm": 0.5723684210526315, "acc_norm_stderr": 0.04026097083296563 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5849056603773585, "acc_stderr": 0.03032594578928611, "acc_norm": 0.5849056603773585, "acc_norm_stderr": 0.03032594578928611 }, "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": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5491329479768786, "acc_stderr": 0.03794012674697031, "acc_norm": 0.5491329479768786, "acc_norm_stderr": 0.03794012674697031 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.29411764705882354, "acc_stderr": 0.045338381959297736, "acc_norm": 0.29411764705882354, "acc_norm_stderr": 0.045338381959297736 }, "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": 0.5276595744680851, "acc_stderr": 0.03263597118409769, "acc_norm": 0.5276595744680851, "acc_norm_stderr": 0.03263597118409769 }, "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": 0.5793103448275863, "acc_stderr": 0.0411391498118926, "acc_norm": 0.5793103448275863, "acc_norm_stderr": 0.0411391498118926 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41798941798941797, "acc_stderr": 0.025402555503260912, "acc_norm": 0.41798941798941797, "acc_norm_stderr": 0.025402555503260912 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.36507936507936506, "acc_stderr": 0.04306241259127153, "acc_norm": 0.36507936507936506, "acc_norm_stderr": 0.04306241259127153 }, "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": 0.6709677419354839, "acc_stderr": 0.026729499068349958, "acc_norm": 0.6709677419354839, "acc_norm_stderr": 0.026729499068349958 }, "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": 0.65, "acc_stderr": 0.0479372485441102, "acc_norm": 0.65, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6363636363636364, "acc_stderr": 0.03756335775187899, "acc_norm": 0.6363636363636364, "acc_norm_stderr": 0.03756335775187899 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.702020202020202, "acc_stderr": 0.03258630383836556, "acc_norm": 0.702020202020202, "acc_norm_stderr": 0.03258630383836556 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7616580310880829, "acc_stderr": 0.030748905363909895, "acc_norm": 0.7616580310880829, "acc_norm_stderr": 0.030748905363909895 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5461538461538461, "acc_stderr": 0.025242770987126177, "acc_norm": 0.5461538461538461, "acc_norm_stderr": 0.025242770987126177 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.31851851851851853, "acc_stderr": 0.028406533090608463, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.02