open-llm-leaderboard-old/details_VAGOsolutions__SauerkrautLM-Gemma-2b

该数据集是在Open LLM Leaderboard上对模型VAGOsolutions/SauerkrautLM-Gemma-2b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。数据集包含1次运行的结果，每次运行都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的额外配置存储了所有运行的聚合结果，这些结果用于计算和展示Open LLM Leaderboard上的聚合指标。README还提供了如何使用`datasets`库中的`load_dataset`函数加载运行详情的示例。

原始信息汇总

数据集概述

该数据集是在对模型 VAGOsolutions/SauerkrautLM-Gemma-2b 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集组成

• 该数据集包含 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。
• 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_VAGOsolutions__SauerkrautLM-Gemma-2b", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-07T11:21:01.848225 运行的最新结果：

python { "all": { "acc": 0.4326218368854279, "acc_stderr": 0.03453943816113397, "acc_norm": 0.4348196750959416, "acc_norm_stderr": 0.03527423254596711, "mc1": 0.23745410036719705, "mc1_stderr": 0.014896277441041836, "mc2": 0.3577128173787486, "mc2_stderr": 0.013537359899643709 }, "harness|arc:challenge|25": { "acc": 0.45563139931740615, "acc_stderr": 0.014553749939306864, "acc_norm": 0.4872013651877133, "acc_norm_stderr": 0.014606603181012534 }, "harness|hellaswag|10": { "acc": 0.5340569607647879, "acc_stderr": 0.004978192893406274, "acc_norm": 0.7141007767377017, "acc_norm_stderr": 0.00450918191932284 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.22, "acc_stderr": 0.04163331998932269, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932269 }, "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": 0.4473684210526316, "acc_stderr": 0.04046336883978251, "acc_norm": 0.4473684210526316, "acc_norm_stderr": 0.04046336883978251 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4981132075471698, "acc_stderr": 0.030772653642075664, "acc_norm": 0.4981132075471698, "acc_norm_stderr": 0.030772653642075664 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4861111111111111, "acc_stderr": 0.04179596617581, "acc_norm": 0.4861111111111111, "acc_norm_stderr": 0.04179596617581 }, "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": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "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": 0.4046242774566474, "acc_stderr": 0.03742461193887248, "acc_norm": 0.4046242774566474, "acc_norm_stderr": 0.03742461193887248 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.19607843137254902, "acc_stderr": 0.03950581861179961, "acc_norm": 0.19607843137254902, "acc_norm_stderr": 0.03950581861179961 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3617021276595745, "acc_stderr": 0.03141082197596239, "acc_norm": 0.3617021276595745, "acc_norm_stderr": 0.03141082197596239 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2982456140350877, "acc_stderr": 0.04303684033537315, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.04303684033537315 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.43448275862068964, "acc_stderr": 0.04130740879555497, "acc_norm": 0.43448275862068964, "acc_norm_stderr": 0.04130740879555497 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2962962962962963, "acc_stderr": 0.02351729433596328, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.02351729433596328 }, "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": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4935483870967742, "acc_stderr": 0.02844163823354051, "acc_norm": 0.4935483870967742, "acc_norm_stderr": 0.02844163823354051 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3891625615763547, "acc_stderr": 0.034304624161038716, "acc_norm": 0.3891625615763547, "acc_norm_stderr": 0.034304624161038716 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.45454545454545453, "acc_stderr": 0.03888176921674098, "acc_norm": 0.45454545454545453, "acc_norm_stderr": 0.03888176921674098 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5, "acc_stderr": 0.035623524993954825, "acc_norm": 0.5, "acc_norm_stderr": 0.035623524993954825 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5751295336787565, "acc_stderr": 0.0356747133521254, "acc_norm": 0.5751295336787565, "acc_norm_stderr": 0.0356747133521254 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.3769230769230769, "acc_stderr": 0.024570975364225995, "acc_norm": 0.3769230769230769, "acc_norm_stderr": 0.024570975364225995 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.23703703703703705, "acc_stderr": 0.025928876132766107, "acc_norm": 0.23703703703703705, "acc_norm_stderr": 0.025928876132766107 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.3865546218487395, "acc_stderr": 0.03