open-llm-leaderboard-old/details_fangloveskari__Dolphin_ORCA_LLaMA_70b_QLoRA

该数据集是在模型fangloveskari/Dolphin_ORCA_LLaMA_70b_QLoRA在Open LLM Leaderboard上的评估运行期间自动创建的。数据集由61个配置组成，每个配置对应一个被评估的任务。数据集是从1次运行中创建的，每次运行在每个配置中作为一个特定的分割找到，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还提供了一个如何使用Python中的datasets库加载运行细节的示例。

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fangloveskari/Dolphin_ORCA_LLaMA_70b_QLoRA在Open LLM Leaderboard上的自动创建的。数据集包含61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。

数据集结构

• 配置数量: 61个配置
• 分割方式: 每个配置包含多个分割，分割名称使用运行的时间戳，"train"分割指向最新结果
• 额外配置: "results"配置存储所有运行的聚合结果，用于计算和显示聚合指标在Open LLM Leaderboard上

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_fangloveskari__Dolphin_ORCA_LLaMA_70b_QLoRA", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是最新结果来自2023-08-30T03:08:37.403827的摘要: python { "all": { "acc": 0.7016950821019889, "acc_stderr": 0.03100773424505602, "acc_norm": 0.7055688798324372, "acc_norm_stderr": 0.030976198338743925, "mc1": 0.4528763769889841, "mc1_stderr": 0.01742558984831402, "mc2": 0.6337134354987094, "mc2_stderr": 0.014897273290786066 }, "harness|arc:challenge|25": { "acc": 0.6834470989761092, "acc_stderr": 0.01359243151906808, "acc_norm": 0.7226962457337884, "acc_norm_stderr": 0.013082095839059374 }, "harness|hellaswag|10": { "acc": 0.6881099382593109, "acc_stderr": 0.004623184227344766, "acc_norm": 0.877414857598088, "acc_norm_stderr": 0.0032729014349397656 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6444444444444445, "acc_stderr": 0.04135176749720385, "acc_norm": 0.6444444444444445, "acc_norm_stderr": 0.04135176749720385 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8026315789473685, "acc_stderr": 0.03238981601699397, "acc_norm": 0.8026315789473685, "acc_norm_stderr": 0.03238981601699397 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7471698113207547, "acc_stderr": 0.026749899771241214, "acc_norm": 0.7471698113207547, "acc_norm_stderr": 0.026749899771241214 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8263888888888888, "acc_stderr": 0.031674733837957166, "acc_norm": 0.8263888888888888, "acc_norm_stderr": 0.031674733837957166 }, "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": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6647398843930635, "acc_stderr": 0.03599586301247077, "acc_norm": 0.6647398843930635, "acc_norm_stderr": 0.03599586301247077 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.77, "acc_stderr": 0.042295258468165065, "acc_norm": 0.77, "acc_norm_stderr": 0.042295258468165065 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6851063829787234, "acc_stderr": 0.030363582197238167, "acc_norm": 0.6851063829787234, "acc_norm_stderr": 0.030363582197238167 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.45614035087719296, "acc_stderr": 0.04685473041907789, "acc_norm": 0.45614035087719296, "acc_norm_stderr": 0.04685473041907789 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6413793103448275, "acc_stderr": 0.03996629574876719, "acc_norm": 0.6413793103448275, "acc_norm_stderr": 0.03996629574876719 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.47883597883597884, "acc_stderr": 0.025728230952130723, "acc_norm": 0.47883597883597884, "acc_norm_stderr": 0.025728230952130723 }, "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": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8096774193548387, "acc_stderr": 0.022331707611823074, "acc_norm": 0.8096774193548387, "acc_norm_stderr": 0.022331707611823074 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.541871921182266, "acc_stderr": 0.03505630140785741, "acc_norm": 0.541871921182266, "acc_norm_stderr": 0.03505630140785741 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.78, "acc_stderr": 0.04163331998932261, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932261 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8484848484848485, "acc_stderr": 0.027998073798781678, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.027998073798781678 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8888888888888888, "acc_stderr": 0.02239078763821677, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.02239078763821677 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9326424870466321, "acc_stderr": 0.0180883938390789, "acc_norm": 0.9326424870466321, "acc_norm_stderr": 0.0180883938390789 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7025641025641025, "acc_stderr": 0.023177408131465946, "acc_norm": 0.7025641025641025, "acc_norm_stderr": 0.023177408131465946 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34444444444444444, "acc_stderr": 0.028972648884844