open-llm-leaderboard-old/details_MediaTek-Research__Breeze-7B-Instruct-v1_0

该数据集是在模型MediaTek-Research/Breeze-7B-Instruct-v1_0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，每个配置对应一个评估任务。它包括1次运行的结果，每次运行作为每个配置中的一个特定分割存储。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，用于计算和显示Open LLM Leaderboard上的聚合指标。文件还提供了如何使用Python中的datasets库加载运行细节的示例。

原始信息汇总

数据集概述

该数据集是在评估模型 MediaTek-Research/Breeze-7B-Instruct-v1_0 在 Open LLM Leaderboard 上的运行过程中自动创建的。

数据集组成

• 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片找到，分片名称使用运行的时间戳。
• "train" 分片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_MediaTek-Research__Breeze-7B-Instruct-v1_0", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-10T11:25:47.003750 运行的最新结果：

python { "all": { "acc": 0.6200291017524624, "acc_stderr": 0.03261202866010721, "acc_norm": 0.6244050267267706, "acc_norm_stderr": 0.03326758975766638, "mc1": 0.3635250917992656, "mc1_stderr": 0.01683886288396583, "mc2": 0.5345540809819518, "mc2_stderr": 0.01524412207520384 }, "harness|arc:challenge|25": { "acc": 0.5836177474402731, "acc_stderr": 0.014405618279436176, "acc_norm": 0.613481228668942, "acc_norm_stderr": 0.014230084761910473 }, "harness|hellaswag|10": { "acc": 0.6288587930691097, "acc_stderr": 0.0048212280346248415, "acc_norm": 0.8259310894244174, "acc_norm_stderr": 0.003783938150151617 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252606, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252606 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5777777777777777, "acc_stderr": 0.04266763404099582, "acc_norm": 0.5777777777777777, "acc_norm_stderr": 0.04266763404099582 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6381578947368421, "acc_stderr": 0.03910525752849724, "acc_norm": 0.6381578947368421, "acc_norm_stderr": 0.03910525752849724 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6943396226415094, "acc_stderr": 0.028353298073322663, "acc_norm": 0.6943396226415094, "acc_norm_stderr": 0.028353298073322663 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7013888888888888, "acc_stderr": 0.03827052357950756, "acc_norm": 0.7013888888888888, "acc_norm_stderr": 0.03827052357950756 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.630057803468208, "acc_stderr": 0.0368122963339432, "acc_norm": 0.630057803468208, "acc_norm_stderr": 0.0368122963339432 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.35294117647058826, "acc_stderr": 0.047551296160629475, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.047551296160629475 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5319148936170213, "acc_stderr": 0.03261936918467381, "acc_norm": 0.5319148936170213, "acc_norm_stderr": 0.03261936918467381 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.47368421052631576, "acc_stderr": 0.046970851366478626, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.046970851366478626 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5724137931034483, "acc_stderr": 0.041227371113703316, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.041227371113703316 }, "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": 0.38095238095238093, "acc_stderr": 0.04343525428949097, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.04343525428949097 }, "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": 0.7419354838709677, "acc_stderr": 0.02489246917246283, "acc_norm": 0.7419354838709677, "acc_norm_stderr": 0.02489246917246283 }, "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": 0.7878787878787878, "acc_stderr": 0.03192271569548301, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.03192271569548301 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7777777777777778, "acc_stderr": 0.029620227874790486, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.029620227874790486 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8601036269430051, "acc_stderr": 0.025033870583015178, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.025033870583015178 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5923076923076923, "acc_stderr": 0.02491524398598785, "acc_norm": 0.5923076923076923, "acc_norm_stderr": 0.02491524398598785 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3111111111111111, "acc_stderr": 0.02822644674968352, "acc_norm": 0.3