open-llm-leaderboard-old/details_abideen__gemma-2b-openhermes

该数据集是在模型abideen/gemma-2b-openhermes在Open LLM Leaderboard上的评估运行期间自动创建的。数据集由63个配置组成，每个配置对应一个被评估的任务。数据集是从一个或多个运行中生成的，每个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。一个名为results的额外配置存储了运行的所有聚合结果，这些结果用于计算和显示Open LLM Leaderboard上的聚合指标。README还提供了一个示例，展示了如何使用Python中的datasets库加载运行中的详细信息。README中还包含了特定运行的最新结果，显示了不同任务的各种准确性指标。

原始信息汇总

数据集概述

该数据集是在模型 abideen/gemma-2b-openhermes 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拆分，拆分名称使用运行的时间戳。
• "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_abideen__gemma-2b-openhermes", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-22T12:05:01.077115 运行的最新结果：

python { "all": { "acc": 0.37696524742191334, "acc_stderr": 0.03381316358729798, "acc_norm": 0.3815378335823341, "acc_norm_stderr": 0.03461953317836164, "mc1": 0.29008567931456547, "mc1_stderr": 0.01588623687420952, "mc2": 0.458323806326475, "mc2_stderr": 0.015931044127458407 }, "harness|arc:challenge|25": { "acc": 0.4044368600682594, "acc_stderr": 0.014342036483436172, "acc_norm": 0.439419795221843, "acc_norm_stderr": 0.01450374782358013 }, "harness|hellaswag|10": { "acc": 0.4810794662417845, "acc_stderr": 0.00498620758186293, "acc_norm": 0.627365066719777, "acc_norm_stderr": 0.004825179407757572 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.3851851851851852, "acc_stderr": 0.042039210401562783, "acc_norm": 0.3851851851851852, "acc_norm_stderr": 0.042039210401562783 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.3355263157894737, "acc_stderr": 0.03842498559395269, "acc_norm": 0.3355263157894737, "acc_norm_stderr": 0.03842498559395269 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.48, "acc_stderr": 0.05021167315686779, "acc_norm": 0.48, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.42641509433962266, "acc_stderr": 0.030437794342983042, "acc_norm": 0.42641509433962266, "acc_norm_stderr": 0.030437794342983042 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3402777777777778, "acc_stderr": 0.03962135573486219, "acc_norm": 0.3402777777777778, "acc_norm_stderr": 0.03962135573486219 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.26, "acc_stderr": 0.04408440022768077, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768077 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3583815028901734, "acc_stderr": 0.036563436533531585, "acc_norm": 0.3583815028901734, "acc_norm_stderr": 0.036563436533531585 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.18627450980392157, "acc_stderr": 0.038739587141493524, "acc_norm": 0.18627450980392157, "acc_norm_stderr": 0.038739587141493524 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.35319148936170214, "acc_stderr": 0.031245325202761923, "acc_norm": 0.35319148936170214, "acc_norm_stderr": 0.031245325202761923 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2807017543859649, "acc_stderr": 0.042270544512322, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.042270544512322 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.46206896551724136, "acc_stderr": 0.04154659671707546, "acc_norm": 0.46206896551724136, "acc_norm_stderr": 0.04154659671707546 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.24867724867724866, "acc_stderr": 0.022261817692400168, "acc_norm": 0.24867724867724866, "acc_norm_stderr": 0.022261817692400168 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604674, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604674 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.3161290322580645, "acc_stderr": 0.02645087448904277, "acc_norm": 0.3161290322580645, "acc_norm_stderr": 0.02645087448904277 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.29064039408866993, "acc_stderr": 0.0319474007226554, "acc_norm": 0.29064039408866993, "acc_norm_stderr": 0.0319474007226554 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.46060606060606063, "acc_stderr": 0.03892207016552012, "acc_norm": 0.46060606060606063, "acc_norm_stderr": 0.03892207016552012 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4595959595959596, "acc_stderr": 0.035507024651313425, "acc_norm": 0.4595959595959596, "acc_norm_stderr": 0.035507024651313425 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.47668393782383417, "acc_stderr": 0.03604513672442207, "acc_norm": 0.47668393782383417, "acc_norm_stderr": 0.03604513672442207 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.3282051282051282, "acc_stderr": 0.023807633198657262, "acc_norm": 0.3282051282051282, "acc_norm_stderr": 0.023807633198657262 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2, "acc_stderr": 0.024388430433987664, "acc_norm": 0.2, "acc_norm_stderr": 0.024388430433987664 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0