open-llm-leaderboard-old/details_fierysurf__Ambari-7B-base-v0.1-sharded

该数据集是在模型 fierysurf/Ambari-7B-base-v0.1-sharded 在 Open LLM Leaderboard 上进行评估时自动创建的。数据集由 63 个配置组成，每个配置对应一个被评估的任务。数据集包含一次运行的结果，每次运行都作为一个特定的分割，分割名称使用运行的时间戳。train 分割始终指向最新的结果。一个名为 results 的额外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。README 还提供了如何使用 Hugging Face datasets 库加载数据集的示例，并包含了特定运行的最新结果。

原始信息汇总

数据集概述

数据集摘要

该数据集是在评估模型fierysurf/Ambari-7B-base-v0.1-sharded在Open LLM Leaderboard上的运行过程中自动创建的。

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。
• 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_fierysurf__Ambari-7B-base-v0.1-sharded", "harness_winogrande_5", split="train")

最新结果

以下是2024-01-18T14:24:01.960531运行的最新结果：

python { "all": { "acc": 0.405829534710468, "acc_stderr": 0.034221917154898474, "acc_norm": 0.4109431400494777, "acc_norm_stderr": 0.03510054355301299, "mc1": 0.23378212974296206, "mc1_stderr": 0.014816195991931576, "mc2": 0.3891001339071866, "mc2_stderr": 0.013756179587991524 }, "harness|arc:challenge|25": { "acc": 0.4462457337883959, "acc_stderr": 0.014526705548539982, "acc_norm": 0.47952218430034127, "acc_norm_stderr": 0.014599131353035007 }, "harness|hellaswag|10": { "acc": 0.5528779127663812, "acc_stderr": 0.004961799358836434, "acc_norm": 0.7461661023700458, "acc_norm_stderr": 0.004343142545094248 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4074074074074074, "acc_stderr": 0.04244633238353228, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.04244633238353228 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.32894736842105265, "acc_stderr": 0.038234289699266046, "acc_norm": 0.32894736842105265, "acc_norm_stderr": 0.038234289699266046 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.41509433962264153, "acc_stderr": 0.03032594578928611, "acc_norm": 0.41509433962264153, "acc_norm_stderr": 0.03032594578928611 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3819444444444444, "acc_stderr": 0.040629907841466674, "acc_norm": 0.3819444444444444, "acc_norm_stderr": 0.040629907841466674 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.28, "acc_stderr": 0.04512608598542127, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3352601156069364, "acc_stderr": 0.03599586301247077, "acc_norm": 0.3352601156069364, "acc_norm_stderr": 0.03599586301247077 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237655, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237655 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3702127659574468, "acc_stderr": 0.03156564682236785, "acc_norm": 0.3702127659574468, "acc_norm_stderr": 0.03156564682236785 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2543859649122807, "acc_stderr": 0.040969851398436716, "acc_norm": 0.2543859649122807, "acc_norm_stderr": 0.040969851398436716 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.33793103448275863, "acc_stderr": 0.039417076320648906, "acc_norm": 0.33793103448275863, "acc_norm_stderr": 0.039417076320648906 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2724867724867725, "acc_stderr": 0.022930973071633356, "acc_norm": 0.2724867724867725, "acc_norm_stderr": 0.022930973071633356 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2222222222222222, "acc_stderr": 0.037184890068181146, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.037184890068181146 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4161290322580645, "acc_stderr": 0.028040981380761547, "acc_norm": 0.4161290322580645, "acc_norm_stderr": 0.028040981380761547 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33004926108374383, "acc_stderr": 0.033085304262282574, "acc_norm": 0.33004926108374383, "acc_norm_stderr": 0.033085304262282574 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5151515151515151, "acc_stderr": 0.03902551007374449, "acc_norm": 0.5151515151515151, "acc_norm_stderr": 0.03902551007374449 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5303030303030303, "acc_stderr": 0.03555804051763929, "acc_norm": 0.5303030303030303, "acc_norm_stderr": 0.03555804051763929 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5440414507772021, "acc_stderr": 0.03594413711272437, "acc_norm": 0.5440414507772021, "acc_norm_stderr": 0.03594413711272437 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.38461538461538464, "acc_stderr": 0.02466674491518722, "acc_norm": 0.38461538461538464, "acc_norm_stderr": 0.02466674491518722 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.25555555555555554, "acc_stderr": 0.026593939101844082, "acc