open-llm-leaderboard/details_GeneZC__MiniChat-3B

该数据集是在Open LLM Leaderboard上对模型GeneZC/MiniChat-3B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。数据集包含一次运行的结果，每次运行在每个配置中表示为特定的分割，train分割始终指向最新结果。此外，results配置存储了所有运行的聚合结果，用于在Open LLM Leaderboard上计算和显示聚合指标。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，并包含了特定运行的最新结果。

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 GeneZC/MiniChat-3B 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集结构

• 配置数量：64个配置，每个配置对应一个评估任务。
• 运行次数：数据集从1次运行中创建。每个运行在每个配置中作为一个特定的分片存在，分片名称使用运行的时间戳。
• 最新结果："train" 分片始终指向最新的结果。
• 聚合结果：一个额外的配置 "results" 存储所有运行的聚合结果，用于计算和显示在 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_GeneZC__MiniChat-3B_public", "harness_winogrande_5", split="train")

最新结果

以下是 2023-11-14T06:58:01.841910 运行 的最新结果： python { "all": { "acc": 0.393327169905453, "acc_stderr": 0.03412443225084784, "acc_norm": 0.3972918823842517, "acc_norm_stderr": 0.03490805641301947, "mc1": 0.2962056303549572, "mc1_stderr": 0.015983595101811396, "mc2": 0.45665988661146706, "mc2_stderr": 0.014686429929550975, "em": 0.2337458053691275, "em_stderr": 0.004334090712150979, "f1": 0.2873447986577185, "f1_stderr": 0.004345675107448542 }, "harness|arc:challenge|25": { "acc": 0.4112627986348123, "acc_stderr": 0.01437944106852208, "acc_norm": 0.4402730375426621, "acc_norm_stderr": 0.014506769524804243 }, "harness|hellaswag|10": { "acc": 0.4955188209520016, "acc_stderr": 0.004989581008163206, "acc_norm": 0.6718781119298944, "acc_norm_stderr": 0.004685698752104812 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4, "acc_stderr": 0.04232073695151589, "acc_norm": 0.4, "acc_norm_stderr": 0.04232073695151589 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.40131578947368424, "acc_stderr": 0.039889037033362836, "acc_norm": 0.40131578947368424, "acc_norm_stderr": 0.039889037033362836 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4830188679245283, "acc_stderr": 0.030755120364119898, "acc_norm": 0.4830188679245283, "acc_norm_stderr": 0.030755120364119898 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4305555555555556, "acc_stderr": 0.04140685639111502, "acc_norm": 0.4305555555555556, "acc_norm_stderr": 0.04140685639111502 }, "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": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.34104046242774566, "acc_stderr": 0.036146654241808254, "acc_norm": 0.34104046242774566, "acc_norm_stderr": 0.036146654241808254 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617746, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617746 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.34893617021276596, "acc_stderr": 0.031158522131357794, "acc_norm": 0.34893617021276596, "acc_norm_stderr": 0.031158522131357794 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.22807017543859648, "acc_stderr": 0.03947152782669415, "acc_norm": 0.22807017543859648, "acc_norm_stderr": 0.03947152782669415 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.3724137931034483, "acc_stderr": 0.0402873153294756, "acc_norm": 0.3724137931034483, "acc_norm_stderr": 0.0402873153294756 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.24867724867724866, "acc_stderr": 0.022261817692400175, "acc_norm": 0.24867724867724866, "acc_norm_stderr": 0.022261817692400175 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604673, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604673 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.3903225806451613, "acc_stderr": 0.027751256636969573, "acc_norm": 0.3903225806451613, "acc_norm_stderr": 0.027751256636969573 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.32019704433497537, "acc_stderr": 0.032826493853041504, "acc_norm": 0.32019704433497537, "acc_norm_stderr": 0.032826493853041504 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.509090909090909, "acc_stderr": 0.039036986477484416, "acc_norm": 0.509090909090909, "acc_norm_stderr": 0.039036986477484416 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4898989898989899, "acc_stderr": 0.035616254886737454, "acc_norm": 0.4898989898989899, "acc_norm_stderr": 0.035616254886737454 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.46113989637305697, "acc_stderr": 0.03597524411734578, "acc_norm": 0.46113989637305697, "acc_norm_stderr": 0.03597524411734578 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.37435897435897436, "acc_stderr": 0.024537591572830517, "acc_norm": 0.37435897435897436, "acc_norm_stderr": 0.024537591572830517 }, "harness|hendrycks