open-llm-leaderboard-old/details_frankenmerger__delta-4b-orange

该数据集是在模型 frankenmerger/delta-4b-orange 在 Open LLM Leaderboard 上的评估运行期间自动创建的。它由 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，每次运行作为每个配置中的一个特定拆分，使用运行的时间戳命名。train 拆分始终指向最新结果。一个额外的配置 results 存储了运行的所有聚合结果，用于计算和显示 Open LLM Leaderboard 上的聚合指标。可以使用 datasets 库中的 load_dataset 函数加载该数据集。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 frankenmerger/delta-4b-orange 的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。
• 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_frankenmerger__delta-4b-orange", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-10T11:41:06.975310 运行的最新结果：

python { "all": { "acc": 0.5672998500589107, "acc_stderr": 0.03374547957816994, "acc_norm": 0.568767763482637, "acc_norm_stderr": 0.0344408518430215, "mc1": 0.401468788249694, "mc1_stderr": 0.017160273901693654, "mc2": 0.5681886396364959, "mc2_stderr": 0.015914705006773194 }, "harness|arc:challenge|25": { "acc": 0.568259385665529, "acc_stderr": 0.014474591427196202, "acc_norm": 0.5887372013651877, "acc_norm_stderr": 0.014379441068522089 }, "harness|hellaswag|10": { "acc": 0.5881298546106354, "acc_stderr": 0.004911659884506146, "acc_norm": 0.7658832901812388, "acc_norm_stderr": 0.004225800787050875 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4888888888888889, "acc_stderr": 0.04318275491977976, "acc_norm": 0.4888888888888889, "acc_norm_stderr": 0.04318275491977976 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5657894736842105, "acc_stderr": 0.040335656678483205, "acc_norm": 0.5657894736842105, "acc_norm_stderr": 0.040335656678483205 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5811320754716981, "acc_stderr": 0.030365050829115208, "acc_norm": 0.5811320754716981, "acc_norm_stderr": 0.030365050829115208 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5833333333333334, "acc_stderr": 0.04122728707651282, "acc_norm": 0.5833333333333334, "acc_norm_stderr": 0.04122728707651282 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.49, "acc_stderr": 0.05024183937956913, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956913 }, "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": 0.5549132947976878, "acc_stderr": 0.03789401760283647, "acc_norm": 0.5549132947976878, "acc_norm_stderr": 0.03789401760283647 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.29411764705882354, "acc_stderr": 0.04533838195929775, "acc_norm": 0.29411764705882354, "acc_norm_stderr": 0.04533838195929775 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4808510638297872, "acc_stderr": 0.03266204299064678, "acc_norm": 0.4808510638297872, "acc_norm_stderr": 0.03266204299064678 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.044346007015849245, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.044346007015849245 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.41379310344827586, "acc_stderr": 0.04104269211806232, "acc_norm": 0.41379310344827586, "acc_norm_stderr": 0.04104269211806232 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42592592592592593, "acc_stderr": 0.02546714904546955, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.02546714904546955 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6580645161290323, "acc_stderr": 0.02698528957655274, "acc_norm": 0.6580645161290323, "acc_norm_stderr": 0.02698528957655274 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.43842364532019706, "acc_stderr": 0.03491207857486518, "acc_norm": 0.43842364532019706, "acc_norm_stderr": 0.03491207857486518 }, "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": 0.7151515151515152, "acc_stderr": 0.03524390844511781, "acc_norm": 0.7151515151515152, "acc_norm_stderr": 0.03524390844511781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7272727272727273, "acc_stderr": 0.03173071239071724, "acc_norm": 0.7272727272727273, "acc_norm_stderr": 0.03173071239071724 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8238341968911918, "acc_stderr": 0.027493504244548057, "acc_norm": 0.8238341968911918, "acc_norm_stderr": 0.027493504244548057 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6025641025641025, "acc_stderr": 0.024811920017903836, "acc_norm": 0.6025641025641025, "acc_norm_stderr": 0.024811920017903836 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2777777777777778, "acc_stderr": 0.02730914058823017, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.027309140