open-llm-leaderboard-old/details_wang7776__vicuna-7b-v1.3-sparsity-10

该数据集是在Open LLM Leaderboard上对模型wang7776/vicuna-7b-v1.3-sparsity-10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。数据集从1次运行中创建，每次运行可以在每个配置中找到，运行的时间戳作为分割的名称。train分割始终指向最新的结果。此外，还有一个名为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

数据集名称

Evaluation run of wang7776/vicuna-7b-v1.3-sparsity-10

数据集描述

该数据集是在评估模型 wang7776/vicuna-7b-v1.3-sparsity-10 在 Open LLM Leaderboard 上的运行过程中自动创建的。

数据集结构

• 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。
• 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_wang7776__vicuna-7b-v1.3-sparsity-10", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-18T11:22:25.072953 运行的最新结果：

python { "all": { "acc": 0.47881736198022445, "acc_stderr": 0.03436036561115092, "acc_norm": 0.48497893053921287, "acc_norm_stderr": 0.03513680059331847, "mc1": 0.31211750305997554, "mc1_stderr": 0.01622075676952092, "mc2": 0.46883380227445837, "mc2_stderr": 0.015097398934278281 }, "harness|arc:challenge|25": { "acc": 0.47013651877133106, "acc_stderr": 0.0145853058400071, "acc_norm": 0.514505119453925, "acc_norm_stderr": 0.014605241081370053 }, "harness|hellaswag|10": { "acc": 0.5793666600278828, "acc_stderr": 0.004926518439372264, "acc_norm": 0.7697669786895041, "acc_norm_stderr": 0.004201215520808244 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.045126085985421296, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421296 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4666666666666667, "acc_stderr": 0.043097329010363554, "acc_norm": 0.4666666666666667, "acc_norm_stderr": 0.043097329010363554 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4605263157894737, "acc_stderr": 0.04056242252249033, "acc_norm": 0.4605263157894737, "acc_norm_stderr": 0.04056242252249033 }, "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": 0.539622641509434, "acc_stderr": 0.03067609659938918, "acc_norm": 0.539622641509434, "acc_norm_stderr": 0.03067609659938918 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4861111111111111, "acc_stderr": 0.04179596617581, "acc_norm": 0.4861111111111111, "acc_norm_stderr": 0.04179596617581 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.35, "acc_stderr": 0.047937248544110175, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110175 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "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": 0.4277456647398844, "acc_stderr": 0.03772446857518026, "acc_norm": 0.4277456647398844, "acc_norm_stderr": 0.03772446857518026 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2549019607843137, "acc_stderr": 0.043364327079931785, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.043364327079931785 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3617021276595745, "acc_stderr": 0.031410821975962386, "acc_norm": 0.3617021276595745, "acc_norm_stderr": 0.031410821975962386 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.21052631578947367, "acc_stderr": 0.038351539543994194, "acc_norm": 0.21052631578947367, "acc_norm_stderr": 0.038351539543994194 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4413793103448276, "acc_stderr": 0.04137931034482758, "acc_norm": 0.4413793103448276, "acc_norm_stderr": 0.04137931034482758 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3253968253968254, "acc_stderr": 0.024130158299762613, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.024130158299762613 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.31746031746031744, "acc_stderr": 0.04163453031302859, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.04163453031302859 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5161290322580645, "acc_stderr": 0.028429203176724555, "acc_norm": 0.5161290322580645, "acc_norm_stderr": 0.028429203176724555 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3645320197044335, "acc_stderr": 0.033864057460620905, "acc_norm": 0.3645320197044335, "acc_norm_stderr": 0.033864057460620905 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5757575757575758, "acc_stderr": 0.03859268142070264, "acc_norm": 0.5757575757575758, "acc_norm_stderr": 0.03859268142070264 }, "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": 0.689119170984456, "acc_stderr": 0.03340361906276585, "acc_norm": 0.689119170984456, "acc_norm_stderr": 0.03340361906276585 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.46923076923076923, "acc_stderr": 0.02530295889085015, "acc_norm": 0.46923076923076923, "acc_norm_stderr": 0.02530295889085015 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.244444444444444