open-llm-leaderboard-old/details_Changgil__K2S3-Mistral-7bx2-48layers_v1.2

该数据集是在模型 Changgil/K2S3-Mistral-7bx2-48layers_v1.2 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，每个配置对应一个评估任务。数据集是从 1 次运行中创建的，每次运行作为每个配置中的一个特定分割。train 分割始终指向最新结果。一个额外的配置 results 存储了所有运行的聚合结果。README 还提供了如何使用 Python 中的 datasets 库加载运行中的详细信息的示例。README 中还包含了 2024-03-29 运行的最新结果。

原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型Changgil/K2S3-Mistral-7bx2-48layers_v1.2在Open LLM Leaderboard上的自动创建的。

数据集结构

• 配置数量：63个配置，每个配置对应一个评估任务。
• 数据来源：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。
• 最新结果："train"分割总是指向最新的结果。
• 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_Changgil__K2S3-Mistral-7bx2-48layers_v1.2", "harness_winogrande_5", split="train")

最新结果

以下是2024-03-29T19:59:03.273138的最新结果：

python { "all": { "acc": 0.579467606046818, "acc_stderr": 0.033372240125975824, "acc_norm": 0.5822000586410329, "acc_norm_stderr": 0.034046612878066436, "mc1": 0.3023255813953488, "mc1_stderr": 0.016077509266133026, "mc2": 0.4612111840396961, "mc2_stderr": 0.015189287391161425 }, "harness|arc:challenge|25": { "acc": 0.5179180887372014, "acc_stderr": 0.014602005585490978, "acc_norm": 0.5631399317406144, "acc_norm_stderr": 0.014494421584256524 }, "harness|hellaswag|10": { "acc": 0.5812587134037045, "acc_stderr": 0.0049234456278615165, "acc_norm": 0.7783310097590121, "acc_norm_stderr": 0.004145206350032319 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5037037037037037, "acc_stderr": 0.04319223625811331, "acc_norm": 0.5037037037037037, "acc_norm_stderr": 0.04319223625811331 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6052631578947368, "acc_stderr": 0.039777499346220734, "acc_norm": 0.6052631578947368, "acc_norm_stderr": 0.039777499346220734 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6377358490566037, "acc_stderr": 0.029582245128384303, "acc_norm": 0.6377358490566037, "acc_norm_stderr": 0.029582245128384303 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6180555555555556, "acc_stderr": 0.040629907841466674, "acc_norm": 0.6180555555555556, "acc_norm_stderr": 0.040629907841466674 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5375722543352601, "acc_stderr": 0.0380168510452446, "acc_norm": 0.5375722543352601, "acc_norm_stderr": 0.0380168510452446 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.30392156862745096, "acc_stderr": 0.04576665403207763, "acc_norm": 0.30392156862745096, "acc_norm_stderr": 0.04576665403207763 }, "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": 0.4723404255319149, "acc_stderr": 0.03263597118409769, "acc_norm": 0.4723404255319149, "acc_norm_stderr": 0.03263597118409769 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3157894736842105, "acc_stderr": 0.04372748290278006, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.04372748290278006 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.38095238095238093, "acc_stderr": 0.025010749116137602, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.025010749116137602 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.38095238095238093, "acc_stderr": 0.043435254289490965, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.043435254289490965 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7225806451612903, "acc_stderr": 0.025470196835900055, "acc_norm": 0.7225806451612903, "acc_norm_stderr": 0.025470196835900055 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.43842364532019706, "acc_stderr": 0.03491207857486518, "acc_norm": 0.43842364532019706, "acc_norm_stderr": 0.03491207857486518 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7393939393939394, "acc_stderr": 0.034277431758165236, "acc_norm": 0.7393939393939394, "acc_norm_stderr": 0.034277431758165236 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7222222222222222, "acc_stderr": 0.03191178226713547, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.03191178226713547 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8082901554404145, "acc_stderr": 0.028408953626245282, "acc_norm": 0.8082901554404145, "acc_norm_stderr": 0.028408953626245282 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6051282051282051, "acc_stderr": 0.0247843169421564, "acc_norm": 0.6051282051282051, "acc_norm_stderr": 0.0247843169421564 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3148148148148148, "acc_stderr":