open-llm-leaderboard-old/details_Gille__StrangeMerges_48-7B-dare_ties

该数据集是在评估模型Gille/StrangeMerges_48-7B-dare_ties在Open LLM Leaderboard上的表现时自动创建的。数据集包含63个配置，每个配置对应一个评估任务。数据集由1次运行生成，每次运行的结果作为特定配置中的一个分割，分割名称使用运行的时间戳命名。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，用于计算和显示在Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 Gille/StrangeMerges_48-7B-dare_ties 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

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。
• 创建来源：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。
• 训练分割："train" 分割始终指向最新的结果。
• 结果配置：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 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_Gille__StrangeMerges_48-7B-dare_ties", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-02T20:33:07.066186 运行的最新结果：

python { "all": { "acc": 0.4968539388371313, "acc_stderr": 0.03444887235423934, "acc_norm": 0.5022418509336306, "acc_norm_stderr": 0.035226049628712106, "mc1": 0.4920440636474908, "mc1_stderr": 0.017501285074551835, "mc2": 0.6554830835773625, "mc2_stderr": 0.015261795466175352 }, "harness|arc:challenge|25": { "acc": 0.5827645051194539, "acc_stderr": 0.014409825518403082, "acc_norm": 0.6092150170648464, "acc_norm_stderr": 0.014258563880513782 }, "harness|hellaswag|10": { "acc": 0.5912168890659231, "acc_stderr": 0.004906043613013399, "acc_norm": 0.8013343955387373, "acc_norm_stderr": 0.003981802822377581 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847415, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847415 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750575, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750575 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5197368421052632, "acc_stderr": 0.040657710025626036, "acc_norm": 0.5197368421052632, "acc_norm_stderr": 0.040657710025626036 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5320754716981132, "acc_stderr": 0.03070948699255655, "acc_norm": 0.5320754716981132, "acc_norm_stderr": 0.03070948699255655 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5694444444444444, "acc_stderr": 0.04140685639111503, "acc_norm": 0.5694444444444444, "acc_norm_stderr": 0.04140685639111503 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5144508670520231, "acc_stderr": 0.03810871630454764, "acc_norm": 0.5144508670520231, "acc_norm_stderr": 0.03810871630454764 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2647058823529412, "acc_stderr": 0.04389869956808777, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.04389869956808777 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.66, "acc_stderr": 0.04760952285695238, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695238 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4085106382978723, "acc_stderr": 0.03213418026701576, "acc_norm": 0.4085106382978723, "acc_norm_stderr": 0.03213418026701576 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.41228070175438597, "acc_stderr": 0.04630653203366596, "acc_norm": 0.41228070175438597, "acc_norm_stderr": 0.04630653203366596 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.47586206896551725, "acc_stderr": 0.041618085035015295, "acc_norm": 0.47586206896551725, "acc_norm_stderr": 0.041618085035015295 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3439153439153439, "acc_stderr": 0.024464426625596426, "acc_norm": 0.3439153439153439, "acc_norm_stderr": 0.024464426625596426 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3412698412698413, "acc_stderr": 0.04240799327574925, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.04240799327574925 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5258064516129032, "acc_stderr": 0.02840609505765332, "acc_norm": 0.5258064516129032, "acc_norm_stderr": 0.02840609505765332 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3793103448275862, "acc_stderr": 0.03413963805906235, "acc_norm": 0.3793103448275862, "acc_norm_stderr": 0.03413963805906235 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.38181818181818183, "acc_stderr": 0.037937131711656344, "acc_norm": 0.38181818181818183, "acc_norm_stderr": 0.037937131711656344 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6212121212121212, "acc_stderr": 0.03456088731993747, "acc_norm": 0.6212121212121212, "acc_norm_stderr": 0.03456088731993747 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7253886010362695, "acc_stderr": 0.03221024508041153, "acc_norm": 0.7253886010362695, "acc_norm_stderr": 0.03221024508041153 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4794871794871795, "acc_stderr": 0.025329663163489943, "acc_norm": 0.4794871794871795, "acc_norm_stderr": 0.025329663163489943 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2518518518518518, "acc_stderr": 0.02646611753895991, "acc_norm": 0.251