open-llm-leaderboard/details_luffycodes__vicuna-shishya-7b-ep3-v1

该数据集是在Open LLM Leaderboard上对模型luffycodes/vicuna-shishya-7b-ep3-v1进行评估时自动创建的。数据集由64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，每次运行都可以在特定配置中找到，分割以运行的时间戳命名。train分割始终指向最新结果。此外，results配置存储了运行的所有聚合结果，并用于计算和显示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集摘要

该数据集是在对模型 luffycodes/vicuna-shishya-7b-ep3-v1 进行评估运行时自动创建的，用于 Open LLM Leaderboard。

数据集组成

• 数据集包含 64 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。
• 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_luffycodes__vicuna-shishya-7b-ep3-v1_public", "harness_winogrande_5", split="train")

最新结果

以下是 2023-11-09T13:24:49.230828 运行的最新结果： python { "all": { "acc": 0.49601218028660454, "acc_stderr": 0.03399727784474729, "acc_norm": 0.5041920928165192, "acc_norm_stderr": 0.03492449912034474, "mc1": 0.2631578947368421, "mc1_stderr": 0.015415241740237012, "mc2": 0.4032424062517679, "mc2_stderr": 0.014739501986326583, "em": 0.2950922818791946, "em_stderr": 0.004670729426706436, "f1": 0.3578932466442965, "f1_stderr": 0.004607902070294773 }, "harness|arc:challenge|25": { "acc": 0.439419795221843, "acc_stderr": 0.014503747823580129, "acc_norm": 0.4590443686006826, "acc_norm_stderr": 0.014562291073601234 }, "harness|hellaswag|10": { "acc": 0.5751842262497511, "acc_stderr": 0.004933047726996794, "acc_norm": 0.7635929097789285, "acc_norm_stderr": 0.004240066898702511 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4868421052631579, "acc_stderr": 0.04067533136309172, "acc_norm": 0.4868421052631579, "acc_norm_stderr": 0.04067533136309172 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5169811320754717, "acc_stderr": 0.030755120364119905, "acc_norm": 0.5169811320754717, "acc_norm_stderr": 0.030755120364119905 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4861111111111111, "acc_stderr": 0.041795966175810016, "acc_norm": 0.4861111111111111, "acc_norm_stderr": 0.041795966175810016 }, "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": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "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": 0.47398843930635837, "acc_stderr": 0.03807301726504511, "acc_norm": 0.47398843930635837, "acc_norm_stderr": 0.03807301726504511 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.16666666666666666, "acc_stderr": 0.03708284662416544, "acc_norm": 0.16666666666666666, "acc_norm_stderr": 0.03708284662416544 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4553191489361702, "acc_stderr": 0.03255525359340355, "acc_norm": 0.4553191489361702, "acc_norm_stderr": 0.03255525359340355 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.04266339443159393, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.04266339443159393 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.45517241379310347, "acc_stderr": 0.04149886942192117, "acc_norm": 0.45517241379310347, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.30158730158730157, "acc_stderr": 0.023636975996101806, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.023636975996101806 }, "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": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.535483870967742, "acc_stderr": 0.02837228779796293, "acc_norm": 0.535483870967742, "acc_norm_stderr": 0.02837228779796293 }, "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": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6424242424242425, "acc_stderr": 0.037425970438065864, "acc_norm": 0.6424242424242425, "acc_norm_stderr": 0.037425970438065864 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5909090909090909, "acc_stderr": 0.03502975799413007, "acc_norm": 0.5909090909090909, "acc_norm_stderr": 0.03502975799413007 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7305699481865285, "acc_stderr": 0.03201867122877794, "acc_norm": 0.7305699481865285, "acc_norm_stderr": 0.03201867122877794 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4307692307692308, "acc_stderr": 0.02510682066053975, "acc_norm": 0.43076923076923