open-llm-leaderboard-old/details_abhishek__autotrain-ixpiv-6kj1e

该数据集是在模型abhishek/autotrain-ixpiv-6kj1e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。数据集来自1次运行，每次运行在每个配置中表示为特定的分割，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。README还提供了如何使用Hugging Face datasets库加载运行中的详细信息的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 abhishek/autotrain-ixpiv-6kj1e 的评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集结构

• 配置数量：63个配置，每个配置对应一个评估任务。
• 数据来源：数据集由1次运行创建，每个运行在每个配置中作为一个特定的分割存在，分割名称使用运行的时间戳。
• 最新结果："train" 分割始终指向最新的结果。
• 结果汇总：一个额外的配置 "results" 存储所有运行的汇总结果，用于计算和显示在 Open LLM Leaderboard 上的汇总指标。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_abhishek__autotrain-ixpiv-6kj1e", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-21T22:05:43.621226 运行的最新结果：

python { "all": { "acc": 0.5805069377691062, "acc_stderr": 0.033161302516735554, "acc_norm": 0.5907084167098668, "acc_norm_stderr": 0.03406273085391777, "mc1": 0.32068543451652387, "mc1_stderr": 0.016339170373280906, "mc2": 0.45718481969610947, "mc2_stderr": 0.015494724297586289 }, "harness|arc:challenge|25": { "acc": 0.5827645051194539, "acc_stderr": 0.014409825518403077, "acc_norm": 0.6168941979522184, "acc_norm_stderr": 0.014206472661672881 }, "harness|hellaswag|10": { "acc": 0.657837084246166, "acc_stderr": 0.004734642167493349, "acc_norm": 0.8254331806413066, "acc_norm_stderr": 0.0037882037293467024 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6074074074074074, "acc_stderr": 0.0421850621536888, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.0421850621536888 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5855263157894737, "acc_stderr": 0.04008973785779205, "acc_norm": 0.5855263157894737, "acc_norm_stderr": 0.04008973785779205 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6754716981132075, "acc_stderr": 0.028815615713432115, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.028815615713432115 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6388888888888888, "acc_stderr": 0.040166600304512336, "acc_norm": 0.6388888888888888, "acc_norm_stderr": 0.040166600304512336 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "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": 0.6127167630057804, "acc_stderr": 0.03714325906302065, "acc_norm": 0.6127167630057804, "acc_norm_stderr": 0.03714325906302065 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4215686274509804, "acc_stderr": 0.04913595201274498, "acc_norm": 0.4215686274509804, "acc_norm_stderr": 0.04913595201274498 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4851063829787234, "acc_stderr": 0.032671518489247764, "acc_norm": 0.4851063829787234, "acc_norm_stderr": 0.032671518489247764 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.41228070175438597, "acc_stderr": 0.046306532033665956, "acc_norm": 0.41228070175438597, "acc_norm_stderr": 0.046306532033665956 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41798941798941797, "acc_stderr": 0.025402555503260912, "acc_norm": 0.41798941798941797, "acc_norm_stderr": 0.025402555503260912 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.04375888492727061, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.04375888492727061 }, "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": 0.6967741935483871, "acc_stderr": 0.026148685930671753, "acc_norm": 0.6967741935483871, "acc_norm_stderr": 0.026148685930671753 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5024630541871922, "acc_stderr": 0.03517945038691063, "acc_norm": 0.5024630541871922, "acc_norm_stderr": 0.03517945038691063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.66, "acc_stderr": 0.04760952285695238, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695238 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6727272727272727, "acc_stderr": 0.03663974994391243, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.03663974994391243 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7424242424242424, "acc_stderr": 0.03115626951964683, "acc_norm": 0.7424242424242424, "acc_norm_stderr": 0.03115626951964683 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8290155440414507, "acc_stderr": 0.027171213683164525, "acc_norm": 0.8290155440414507, "acc_norm_stderr": 0.027171213683164525 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5820512820512821, "acc_stderr": 0.02500732988246122, "acc_norm": 0.5820512820512821, "acc_norm_stderr": 0.02500732988246122 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3148148148148148, "acc_stderr": 0.02831753349606648, "acc_norm