open-llm-leaderboard-old/details_01-ai__Yi-1.5-6B-Chat

该数据集是在模型01-ai/Yi-1.5-6B-Chat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，每个配置对应一个被评估的任务。它包含1次运行的结果，每次运行在每个配置中表示为特定的分割。train分割始终指向最新的结果。此外，还有一个results配置存储了所有运行的聚合结果，这些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`datasets`库中的`load_dataset`函数加载数据集的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在对模型 01-ai/Yi-1.5-6B-Chat 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。
• 数据集来自 1 次运行，每次运行在每个配置中都有一个特定的分割，分割名称使用运行的时间戳。
• "train" 分割始终指向最新的结果。
• 一个额外的配置 "results" 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_01-ai__Yi-1.5-6B-Chat", "harness_winogrande_5", split="train")

最新结果

以下是 最新结果来自 run 2024-05-16T14:12:12.578596 的摘要：

python { "all": { "acc": 0.642607219777573, "acc_stderr": 0.0329109440194826, "acc_norm": 0.6442828622303912, "acc_norm_stderr": 0.03358053367793045, "mc1": 0.3623011015911873, "mc1_stderr": 0.016826646897262258, "mc2": 0.5257270462628132, "mc2_stderr": 0.016013980796101952 }, "harness|arc:challenge|25": { "acc": 0.5776450511945392, "acc_stderr": 0.014434138713379991, "acc_norm": 0.606655290102389, "acc_norm_stderr": 0.014275101465693028 }, "harness|hellaswag|10": { "acc": 0.5974905397331209, "acc_stderr": 0.004894012555642648, "acc_norm": 0.7886875124477196, "acc_norm_stderr": 0.00407405211345136 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5185185185185185, "acc_stderr": 0.043163785995113245, "acc_norm": 0.5185185185185185, "acc_norm_stderr": 0.043163785995113245 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6710526315789473, "acc_stderr": 0.038234289699266046, "acc_norm": 0.6710526315789473, "acc_norm_stderr": 0.038234289699266046 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6792452830188679, "acc_stderr": 0.028727502957880274, "acc_norm": 0.6792452830188679, "acc_norm_stderr": 0.028727502957880274 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7222222222222222, "acc_stderr": 0.03745554791462457, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.03745554791462457 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6069364161849711, "acc_stderr": 0.03724249595817731, "acc_norm": 0.6069364161849711, "acc_norm_stderr": 0.03724249595817731 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.45098039215686275, "acc_stderr": 0.049512182523962625, "acc_norm": 0.45098039215686275, "acc_norm_stderr": 0.049512182523962625 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6468085106382979, "acc_stderr": 0.031245325202761926, "acc_norm": 0.6468085106382979, "acc_norm_stderr": 0.031245325202761926 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6344827586206897, "acc_stderr": 0.04013124195424386, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.04013124195424386 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.5343915343915344, "acc_stderr": 0.025690321762493844, "acc_norm": 0.5343915343915344, "acc_norm_stderr": 0.025690321762493844 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5873015873015873, "acc_stderr": 0.04403438954768177, "acc_norm": 0.5873015873015873, "acc_norm_stderr": 0.04403438954768177 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7580645161290323, "acc_stderr": 0.024362599693031086, "acc_norm": 0.7580645161290323, "acc_norm_stderr": 0.024362599693031086 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5320197044334976, "acc_stderr": 0.03510766597959215, "acc_norm": 0.5320197044334976, "acc_norm_stderr": 0.03510766597959215 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7878787878787878, "acc_stderr": 0.03192271569548301, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.03192271569548301 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7828282828282829, "acc_stderr": 0.029376616484945627, "acc_norm": 0.7828282828282829, "acc_norm_stderr": 0.029376616484945627 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.844559585492228, "acc_stderr": 0.026148483469153327, "acc_norm": 0.844559585492228, "acc_norm_stderr": 0.026148483469153327 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6692307692307692, "acc_stderr": 0.023854795680971128, "acc_norm": 0.6692307692307692, "acc_norm_stderr": 0.023854795680971128 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.42592592592592593, "acc_stderr": 0.03014913560136594, "acc_norm": 0.42592592592592593, "acc_norm_stderr": 0.0301491