open-llm-leaderboard-old/details_Steelskull__Lumosia-v2-MoE-4x10.7

该数据集是在评估模型Steelskull/Lumosia-v2-MoE-4x10.7运行期间自动创建的，用于记录和分析该模型在Open LLM Leaderboard上的表现。数据集由63个配置组成，每个配置对应一个特定的评估任务。每个任务的结果存储在以运行时间戳命名的split中，而train split始终指向最新的结果。此外，results配置存储了所有任务的聚合结果，用于计算和展示Leaderboard上的聚合指标。

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 Steelskull/Lumosia-v2-MoE-4x10.7 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 "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_Steelskull__Lumosia-v2-MoE-4x10.7", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-02T08:19:21.300026 运行的最新结果：

python { "all": { "acc": 0.6680685275478645, "acc_stderr": 0.0315547578178304, "acc_norm": 0.6687810115447916, "acc_norm_stderr": 0.032201365533529785, "mc1": 0.5324357405140759, "mc1_stderr": 0.017466632149577617, "mc2": 0.6847502236527627, "mc2_stderr": 0.015252351834031837 }, "harness|arc:challenge|25": { "acc": 0.6808873720136519, "acc_stderr": 0.013621696119173307, "acc_norm": 0.7039249146757679, "acc_norm_stderr": 0.013340916085246252 }, "harness|hellaswag|10": { "acc": 0.7024497112129058, "acc_stderr": 0.004562462665505232, "acc_norm": 0.8787094204341764, "acc_norm_stderr": 0.003257974593789941 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.42, "acc_stderr": 0.04960449637488583, "acc_norm": 0.42, "acc_norm_stderr": 0.04960449637488583 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6074074074074074, "acc_stderr": 0.04218506215368879, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.04218506215368879 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.743421052631579, "acc_stderr": 0.0355418036802569, "acc_norm": 0.743421052631579, "acc_norm_stderr": 0.0355418036802569 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.74, "acc_stderr": 0.0440844002276808, "acc_norm": 0.74, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7638888888888888, "acc_stderr": 0.03551446610810826, "acc_norm": 0.7638888888888888, "acc_norm_stderr": 0.03551446610810826 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "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": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6170212765957447, "acc_stderr": 0.03177821250236922, "acc_norm": 0.6170212765957447, "acc_norm_stderr": 0.03177821250236922 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5, "acc_stderr": 0.047036043419179864, "acc_norm": 0.5, "acc_norm_stderr": 0.047036043419179864 }, "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": 0.47883597883597884, "acc_stderr": 0.025728230952130733, "acc_norm": 0.47883597883597884, "acc_norm_stderr": 0.025728230952130733 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42857142857142855, "acc_stderr": 0.0442626668137991, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.0442626668137991 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8129032258064516, "acc_stderr": 0.022185710092252255, "acc_norm": 0.8129032258064516, "acc_norm_stderr": 0.022185710092252255 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5172413793103449, "acc_stderr": 0.035158955511656986, "acc_norm": 0.5172413793103449, "acc_norm_stderr": 0.035158955511656986 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8, "acc_stderr": 0.031234752377721175, "acc_norm": 0.8, "acc_norm_stderr": 0.031234752377721175 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9015544041450777, "acc_stderr": 0.021500249576033467, "acc_norm": 0.9015544041450777, "acc_norm_stderr": 0.021500249576033467 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6564102564102564, "acc_stderr": 0.02407869658063547, "acc_norm": 0.6564102564102564, "acc_norm_stderr": 0.02407869658063547 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.35555555555555557, "acc_stderr": 0.02918571494985741, "acc_norm": 0.35555555555555557, "acc_norm_stderr": 0.02918571494985741 }, "harness|hendrycksTest-