open-llm-leaderboard-old/details_wang7776__Llama-2-7b-chat-hf-30-sparsity

该数据集是在模型wang7776/Llama-2-7b-chat-hf-30-sparsity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。它由1次运行创建，每次运行作为每个配置中的特定分割找到，分割名称使用运行的时间戳。train分割始终指向最新结果。一个额外的配置results存储了运行的所有聚合结果，用于计算和显示Open LLM Leaderboard上的聚合指标。README还提供了一个使用Python中的datasets库加载运行细节的示例。

原始信息汇总

数据集概述

数据集摘要

该数据集是在对模型 wang7776/Llama-2-7b-chat-hf-30-sparsity 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。数据集从1次运行中创建，每次运行的详细信息可以在每个配置中找到，使用运行的时间戳作为分割名称。"train" 分割始终指向最新的结果。

数据集结构

• 配置数量: 63
• 分割方式: 每个配置包含特定运行的分割，分割名称使用运行的时间戳。
• 最新结果: "train" 分割指向最新的结果。

额外配置

• "results" 配置: 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_wang7776__Llama-2-7b-chat-hf-30-sparsity", "harness_winogrande_5", split="train")

最新结果

以下是 2023-12-12T03:37:48.728667 运行的最新结果：

python { "all": { "acc": 0.45732892704529104, "acc_stderr": 0.03428010617513505, "acc_norm": 0.4621141078743541, "acc_norm_stderr": 0.035035452136234484, "mc1": 0.2913096695226438, "mc1_stderr": 0.015905987048184828, "mc2": 0.4482303614832581, "mc2_stderr": 0.01566475317876804 }, "harness|arc:challenge|25": { "acc": 0.4786689419795222, "acc_stderr": 0.014598087973127108, "acc_norm": 0.5247440273037542, "acc_norm_stderr": 0.014593487694937742 }, "harness|hellaswag|10": { "acc": 0.5774746066520613, "acc_stderr": 0.004929517011508224, "acc_norm": 0.7657837084246166, "acc_norm_stderr": 0.0042264246245106935 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.04605661864718381, "acc_norm": 0.3, "acc_norm_stderr": 0.04605661864718381 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4074074074074074, "acc_stderr": 0.042446332383532286, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.042446332383532286 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.48026315789473684, "acc_stderr": 0.040657710025626036, "acc_norm": 0.48026315789473684, "acc_norm_stderr": 0.040657710025626036 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4830188679245283, "acc_stderr": 0.030755120364119898, "acc_norm": 0.4830188679245283, "acc_norm_stderr": 0.030755120364119898 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5069444444444444, "acc_stderr": 0.04180806750294938, "acc_norm": 0.5069444444444444, "acc_norm_stderr": 0.04180806750294938 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "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": 0.19607843137254902, "acc_stderr": 0.039505818611799616, "acc_norm": 0.19607843137254902, "acc_norm_stderr": 0.039505818611799616 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.37872340425531914, "acc_stderr": 0.03170995606040655, "acc_norm": 0.37872340425531914, "acc_norm_stderr": 0.03170995606040655 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.32456140350877194, "acc_stderr": 0.044045561573747664, "acc_norm": 0.32456140350877194, "acc_norm_stderr": 0.044045561573747664 }, "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": 0.25925925925925924, "acc_stderr": 0.022569897074918424, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.022569897074918424 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.23015873015873015, "acc_stderr": 0.03764950879790604, "acc_norm": 0.23015873015873015, "acc_norm_stderr": 0.03764950879790604 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5225806451612903, "acc_stderr": 0.02841498501970786, "acc_norm": 0.5225806451612903, "acc_norm_stderr": 0.02841498501970786 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3399014778325123, "acc_stderr": 0.033327690684107895, "acc_norm": 0.3399014778325123, "acc_norm_stderr": 0.033327690684107895 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.593939393939394, "acc_stderr": 0.03834816355401181, "acc_norm": 0.593939393939394, "acc_norm_stderr": 0.03834816355401181 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5959595959595959, "acc_stderr": 0.03496130972056129, "acc_norm": 0.5959595959595959, "acc_norm_stderr": 0.03496130972056129 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6683937823834197, "acc_stderr": 0.03397636541089118, "acc_norm": 0.6683937823834197, "acc_norm_stderr": 0.03397636541089118 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.38461538461538464, "acc_stderr": 0.024666744915187222, "acc_norm": 0.38461538461538464, "acc_norm_stderr": 0.024666744915187222 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.25925925925925924, "acc_stderr": 0.026719240783712177