open-llm-leaderboard-old/details_saucam__aqua-smaug-0.3-8B

该数据集是在模型saucam/aqua-smaug-0.3-8B的评估运行期间自动创建的，用于在Open LLM Leaderboard上进行评估。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。此外，results配置存储了所有运行的聚合结果，并用于计算和显示在Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集简介

该数据集是在对模型 saucam/aqua-smaug-0.3-8B 进行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，每个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。
• 额外的 "results" 配置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_saucam__aqua-smaug-0.3-8B", "harness_winogrande_5", split="train")

最新结果

以下是 最新结果 的摘要： python { "all": { "acc": 0.672840231638175, "acc_stderr": 0.03158255824963486, "acc_norm": 0.674715632751459, "acc_norm_stderr": 0.03221685366999414, "mc1": 0.38555691554467564, "mc1_stderr": 0.01703883901059167, "mc2": 0.5384433999408047, "mc2_stderr": 0.015169364716104286 }, "harness|arc:challenge|25": { "acc": 0.5878839590443686, "acc_stderr": 0.014383915302225405, "acc_norm": 0.6313993174061433, "acc_norm_stderr": 0.0140978106780422 }, "harness|hellaswag|10": { "acc": 0.6350328619796853, "acc_stderr": 0.004804370563856223, "acc_norm": 0.828918542123083, "acc_norm_stderr": 0.0037581050431501253 }, "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": 0.6592592592592592, "acc_stderr": 0.04094376269996793, "acc_norm": 0.6592592592592592, "acc_norm_stderr": 0.04094376269996793 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.743421052631579, "acc_stderr": 0.0355418036802569, "acc_norm": 0.743421052631579, "acc_norm_stderr": 0.0355418036802569 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.67, "acc_stderr": 0.04725815626252607, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252607 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7509433962264151, "acc_stderr": 0.02661648298050171, "acc_norm": 0.7509433962264151, "acc_norm_stderr": 0.02661648298050171 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03476590104304134, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03476590104304134 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.6, "acc_stderr": 0.04923659639173309, "acc_norm": 0.6, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6473988439306358, "acc_stderr": 0.036430371689585475, "acc_norm": 0.6473988439306358, "acc_norm_stderr": 0.036430371689585475 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.49019607843137253, "acc_stderr": 0.04974229460422817, "acc_norm": 0.49019607843137253, "acc_norm_stderr": 0.04974229460422817 }, "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": 0.6, "acc_stderr": 0.03202563076101736, "acc_norm": 0.6, "acc_norm_stderr": 0.03202563076101736 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5526315789473685, "acc_stderr": 0.04677473004491199, "acc_norm": 0.5526315789473685, "acc_norm_stderr": 0.04677473004491199 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6689655172413793, "acc_stderr": 0.039215453124671215, "acc_norm": 0.6689655172413793, "acc_norm_stderr": 0.039215453124671215 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4444444444444444, "acc_stderr": 0.025591857761382182, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.025591857761382182 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5, "acc_stderr": 0.04472135954999579, "acc_norm": 0.5, "acc_norm_stderr": 0.04472135954999579 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7774193548387097, "acc_stderr": 0.023664216671642507, "acc_norm": 0.7774193548387097, "acc_norm_stderr": 0.023664216671642507 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5073891625615764, "acc_stderr": 0.035176035403610105, "acc_norm": 0.5073891625615764, "acc_norm_stderr": 0.035176035403610105 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7575757575757576, "acc_stderr": 0.03346409881055953, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.03346409881055953 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8434343434343434, "acc_stderr": 0.025890520358141454, "acc_norm": 0.8434343434343434, "acc_norm_stderr": 0.025890520358141454 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9119170984455959, "acc_stderr": 0.02045374660160103, "acc_norm": 0.9119170984455959, "acc_norm_stderr": 0.02045374660160103 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6641025641025641, "acc_stderr": 0.023946724741563973, "acc_norm": 0.6641025641025641, "acc_norm_stderr": 0.023946724741563973 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3962962962962963, "acc_stderr": 0.029822619458533994, "acc_norm": 0.3962962962962963, "acc_norm_stderr": 0.029822619458533994 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.7352941176470589, "acc_stderr": 0.02