open-llm-leaderboard-old/details_WhiteRabbitNeo__WhiteRabbitNeo-33B-v1

该数据集是在模型WhiteRabbitNeo/WhiteRabbitNeo-33B-v1在Open LLM Leaderboard上进行评估运行期间自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。它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分割始终指向最新的结果。此外，还有一个results配置，存储了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。README还提供了一个示例，展示了如何使用`datasets`库中的`load_dataset`函数加载运行中的详细信息。还包括了特定运行的最新结果，显示了不同任务的各种指标，如准确率和错误率。

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 WhiteRabbitNeo/WhiteRabbitNeo-33B-v1 在 Open LLM Leaderboard 上的自动创建的。

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。
• 额外的 "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_WhiteRabbitNeo__WhiteRabbitNeo-33B-v1", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-17T09:51:00.139544 运行的最新结果：

python { "all": { "acc": 0.4084433830187643, "acc_stderr": 0.03461298543112304, "acc_norm": 0.40954626519765713, "acc_norm_stderr": 0.03533514396550226, "mc1": 0.26805385556915545, "mc1_stderr": 0.015506204722834555, "mc2": 0.416805939433293, "mc2_stderr": 0.014767283735086846 }, "harness|arc:challenge|25": { "acc": 0.40187713310580203, "acc_stderr": 0.014327268614578276, "acc_norm": 0.44368600682593856, "acc_norm_stderr": 0.014518421825670452 }, "harness|hellaswag|10": { "acc": 0.44831706831308504, "acc_stderr": 0.004963053161193613, "acc_norm": 0.6021708822943637, "acc_norm_stderr": 0.004884495069459711 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.3851851851851852, "acc_stderr": 0.042039210401562783, "acc_norm": 0.3851851851851852, "acc_norm_stderr": 0.042039210401562783 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.3881578947368421, "acc_stderr": 0.03965842097512744, "acc_norm": 0.3881578947368421, "acc_norm_stderr": 0.03965842097512744 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4188679245283019, "acc_stderr": 0.03036505082911521, "acc_norm": 0.4188679245283019, "acc_norm_stderr": 0.03036505082911521 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3699421965317919, "acc_stderr": 0.036812296333943194, "acc_norm": 0.3699421965317919, "acc_norm_stderr": 0.036812296333943194 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.27450980392156865, "acc_stderr": 0.044405219061793254, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.044405219061793254 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3574468085106383, "acc_stderr": 0.03132941789476425, "acc_norm": 0.3574468085106383, "acc_norm_stderr": 0.03132941789476425 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.32456140350877194, "acc_stderr": 0.04404556157374767, "acc_norm": 0.32456140350877194, "acc_norm_stderr": 0.04404556157374767 }, "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": 0.3439153439153439, "acc_stderr": 0.024464426625596437, "acc_norm": 0.3439153439153439, "acc_norm_stderr": 0.024464426625596437 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.432258064516129, "acc_stderr": 0.02818173972001941, "acc_norm": 0.432258064516129, "acc_norm_stderr": 0.02818173972001941 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.31527093596059114, "acc_stderr": 0.03269080871970186, "acc_norm": 0.31527093596059114, "acc_norm_stderr": 0.03269080871970186 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.4727272727272727, "acc_stderr": 0.03898531605579419, "acc_norm": 0.4727272727272727, "acc_norm_stderr": 0.03898531605579419 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4292929292929293, "acc_stderr": 0.035265527246011986, "acc_norm": 0.4292929292929293, "acc_norm_stderr": 0.035265527246011986 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.43523316062176165, "acc_stderr": 0.03578038165008586, "acc_norm": 0.43523316062176165, "acc_norm_stderr": 0.03578038165008586 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.36666666666666664, "acc_stderr": 0.024433016466052452, "acc_norm": 0.36666666666666664, "acc_norm_stderr": 0.024433016466052452 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.28888888888888886, "acc_stderr": 0.027634907264178544,