open-llm-leaderboard-old/details_NeuralNovel__Panda-7B-v0.1

该数据集是在Open LLM Leaderboard上对模型NeuralNovel/Panda-7B-v0.1进行评估时自动创建的。数据集由63个配置组成，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，分割以运行的时间戳命名。train分割始终指向最新结果。此外，一个名为results的配置存储了所有运行的聚合结果，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

数据集名称

Evaluation run of NeuralNovel/Panda-7B-v0.1

数据集摘要

该数据集是在模型NeuralNovel/Panda-7B-v0.1在Open LLM Leaderboard上的评估运行期间自动创建的。

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_NeuralNovel__Panda-7B-v0.1", "harness_winogrande_5", split="train")

最新结果

这些是最新的结果，来自2024-01-04T15:18:35.035620的运行： python { "all": { "acc": 0.6067411577411931, "acc_stderr": 0.03324319692041124, "acc_norm": 0.6115988704639006, "acc_norm_stderr": 0.03391766146815033, "mc1": 0.5214198286413708, "mc1_stderr": 0.01748743214471164, "mc2": 0.6697345091207095, "mc2_stderr": 0.01518186947277888 }, "harness|arc:challenge|25": { "acc": 0.5930034129692833, "acc_stderr": 0.01435639941800912, "acc_norm": 0.6296928327645052, "acc_norm_stderr": 0.01411129875167495 }, "harness|hellaswag|10": { "acc": 0.6520613423620792, "acc_stderr": 0.004753429806645438, "acc_norm": 0.8375821549492133, "acc_norm_stderr": 0.003680798950531901 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.04793724854411021, "acc_norm": 0.35, "acc_norm_stderr": 0.04793724854411021 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5777777777777777, "acc_stderr": 0.04266763404099582, "acc_norm": 0.5777777777777777, "acc_norm_stderr": 0.04266763404099582 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5986842105263158, "acc_stderr": 0.039889037033362836, "acc_norm": 0.5986842105263158, "acc_norm_stderr": 0.039889037033362836 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6716981132075471, "acc_stderr": 0.028901593612411784, "acc_norm": 0.6716981132075471, "acc_norm_stderr": 0.028901593612411784 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6736111111111112, "acc_stderr": 0.03921067198982266, "acc_norm": 0.6736111111111112, "acc_norm_stderr": 0.03921067198982266 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5895953757225434, "acc_stderr": 0.03750757044895537, "acc_norm": 0.5895953757225434, "acc_norm_stderr": 0.03750757044895537 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4117647058823529, "acc_stderr": 0.048971049527263666, "acc_norm": 0.4117647058823529, "acc_norm_stderr": 0.048971049527263666 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.67, "acc_stderr": 0.04725815626252609, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252609 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5106382978723404, "acc_stderr": 0.03267862331014063, "acc_norm": 0.5106382978723404, "acc_norm_stderr": 0.03267862331014063 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.42105263157894735, "acc_stderr": 0.046446020912223177, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.046446020912223177 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6275862068965518, "acc_stderr": 0.04028731532947558, "acc_norm": 0.6275862068965518, "acc_norm_stderr": 0.04028731532947558 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3835978835978836, "acc_stderr": 0.025043757318520193, "acc_norm": 0.3835978835978836, "acc_norm_stderr": 0.025043757318520193 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4126984126984127, "acc_stderr": 0.04403438954768176, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.04403438954768176 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6806451612903226, "acc_stderr": 0.026522709674667765, "acc_norm": 0.6806451612903226, "acc_norm_stderr": 0.026522709674667765 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5123152709359606, "acc_stderr": 0.035169204442208966, "acc_norm": 0.5123152709359606, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7333333333333333, "acc_stderr": 0.03453131801885417, "acc_norm": 0.7333333333333333, "acc_norm_stderr": 0.03453131801885417 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7575757575757576, "acc_stderr": 0.030532892233932022, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.030532892233932022 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.844559585492228, "acc_stderr": 0.026148483469153317, "acc_norm": 0.844559585492228, "acc_norm_stderr": 0.026148483469153317 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5717948717948718, "acc_stderr": 0.02508830145469483, "acc_norm": 0.5717948717948718, "acc_norm_stderr": 0.02508830145469483 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32222222222222224, "acc_stderr": 0.028493465091028593, "acc_norm": 0.32222222222222224, "acc_norm_stderr": 0.028493465091028593 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.63