open-llm-leaderboard-old/details_JCX-kcuf__Llama-2-7b-hf-gpt-3.5-80k

该数据集是在对模型JCX-kcuf/Llama-2-7b-hf-gpt-3.5-80k进行评估运行期间自动创建的。数据集包含63个配置，每个配置对应一个评估任务。数据集由1次运行创建，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。此外，还有一个名为"results"的配置，存储了运行中所有聚合的结果，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

该数据集是在评估模型 JCX-kcuf/Llama-2-7b-hf-gpt-3.5-80k 在 Open LLM Leaderboard 上的自动创建的。数据集包含 63 个配置，每个配置对应一个评估任务。

数据集结构

• 配置数量：63 个配置
• 数据来源：1 次运行结果
• 数据分割：每个配置包含特定分割，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 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_JCX-kcuf__Llama-2-7b-hf-gpt-3.5-80k", "harness_winogrande_5", split="train")

最新结果

最新结果来自 2024-03-28T00:04:47.376277 运行，包含多个任务的准确率和标准误差。以下是部分任务的结果示例：

python { "all": { "acc": 0.46129015263982415, "acc_stderr": 0.034478372271379606, "acc_norm": 0.466156014223618, "acc_norm_stderr": 0.035256245444643106, "mc1": 0.2827417380660955, "mc1_stderr": 0.015764770836777308, "mc2": 0.41421125437928746, "mc2_stderr": 0.014859051283039066 }, "harness|arc:challenge|25": { "acc": 0.5008532423208191, "acc_stderr": 0.014611369529813283, "acc_norm": 0.53839590443686, "acc_norm_stderr": 0.014568245550296358 }, "harness|hellaswag|10": { "acc": 0.5638319059948218, "acc_stderr": 0.004948952519517518, "acc_norm": 0.7577175861382195, "acc_norm_stderr": 0.004275886276011774 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.42962962962962964, "acc_stderr": 0.04276349494376599, "acc_norm": 0.42962962962962964, "acc_norm_stderr": 0.04276349494376599 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.42105263157894735, "acc_stderr": 0.04017901275981749, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.04017901275981749 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4641509433962264, "acc_stderr": 0.030693675018458003, "acc_norm": 0.4641509433962264, "acc_norm_stderr": 0.030693675018458003 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4375, "acc_stderr": 0.04148415739394154, "acc_norm": 0.4375, "acc_norm_stderr": 0.04148415739394154 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4508670520231214, "acc_stderr": 0.037940126746970296, "acc_norm": 0.4508670520231214, "acc_norm_stderr": 0.037940126746970296 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237654, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237654 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.55, "acc_stderr": 0.04999999999999999, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999999 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.43829787234042555, "acc_stderr": 0.032436186361081004, "acc_norm": 0.43829787234042555, "acc_norm_stderr": 0.032436186361081004 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2719298245614035, "acc_stderr": 0.04185774424022056, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.04185774424022056 }, "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": 0.25925925925925924, "acc_stderr": 0.022569897074918407, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.022569897074918407 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3333333333333333, "acc_stderr": 0.042163702135578345, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.042163702135578345 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.26, "acc_stderr": 0.04408440022768079, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.49032258064516127, "acc_stderr": 0.02843867799890955, "acc_norm": 0.49032258064516127, "acc_norm_stderr": 0.02843867799890955 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33004926108374383, "acc_stderr": 0.03308530426228258, "acc_norm": 0.33004926108374383, "acc_norm_stderr": 0.03308530426228258 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6060606060606061, "acc_stderr": 0.03815494308688932, "acc_norm": 0.6060606060606061, "acc_norm_stderr": 0.03815494308688932 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5505050505050505, "acc_stderr": 0.035441324919479704, "acc_norm": 0.5505050505050505, "acc_norm_stderr": 0.035441324919479704 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6321243523316062, "acc_stderr": 0.034801756684660366, "acc_norm": 0.6321243523316062, "acc_norm_stderr": 0.034801756684660366 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.44358974358974357, "acc_stderr": 0.025189149894764198, "acc_norm": 0.44358974358974357, "acc_norm_stderr": 0.025189149894764198 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.24444444444444444, "acc_stderr": 0.026202766534652148, "acc_norm": 0.24444444444444444, "acc_norm_stderr": 0.0262027665346521