open-llm-leaderboard-old/details_Qwen__Qwen1.5-32B-Chat

该数据集是在模型Qwen/Qwen1.5-32B-Chat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。每个配置包含特定分割，这些分割以运行的时间戳命名，其中train分割始终指向最新的结果。此外，还有一个名为results的配置，存储了运行中的所有聚合结果，用于在Leaderboard上计算和显示聚合指标。文件中还包含了用于从特定运行中加载数据集详细信息的Python代码片段。

原始信息汇总

数据集概述

数据集名称

• 名称: Evaluation run of Qwen/Qwen1.5-32B-Chat

数据集描述

• 创建目的: 该数据集是在模型 Qwen/Qwen1.5-32B-Chat 在 Open LLM Leaderboard 上的评估运行期间自动创建的。
• 组成: 数据集包含 63 个配置，每个配置对应一个评估任务。
• 创建来源: 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_Qwen__Qwen1.5-32B-Chat", "harness_winogrande_5", split="train")

最新结果

• 最新结果来源: 最新结果来自 2024-04-05T22:44:54.008135 运行
• 结果示例: python { "all": { "acc": 0.7358455916450526, "acc_stderr": 0.029043683105290544, "acc_norm": 0.7501932941094357, "acc_norm_stderr": 0.02968414049893116, "mc1": 0.4785801713586291, "mc1_stderr": 0.017487432144711813, "mc2": 0.6694777411427348, "mc2_stderr": 0.015419909773015179 }, "harness|arc:challenge|25": { "acc": 0.6296928327645052, "acc_stderr": 0.01411129875167495, "acc_norm": 0.6604095563139932, "acc_norm_stderr": 0.013839039762820169 }, "harness|hellaswag|10": { "acc": 0.6683927504481179, "acc_stderr": 0.004698285350019215, "acc_norm": 0.8549093806014738, "acc_norm_stderr": 0.0035147239847366125 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.44, "acc_stderr": 0.0498887651569859, "acc_norm": 0.44, "acc_norm_stderr": 0.0498887651569859 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6888888888888889, "acc_stderr": 0.039992628766177214, "acc_norm": 0.6888888888888889, "acc_norm_stderr": 0.039992628766177214 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8355263157894737, "acc_stderr": 0.030167533468632723, "acc_norm": 0.8355263157894737, "acc_norm_stderr": 0.030167533468632723 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.81, "acc_stderr": 0.03942772444036623, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036623 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7660377358490567, "acc_stderr": 0.02605529690115292, "acc_norm": 0.7660377358490567, "acc_norm_stderr": 0.02605529690115292 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8680555555555556, "acc_stderr": 0.02830096838204443, "acc_norm": 0.8680555555555556, "acc_norm_stderr": 0.02830096838204443 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.59, "acc_stderr": 0.04943110704237101, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237101 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7630057803468208, "acc_stderr": 0.03242414757483098, "acc_norm": 0.7630057803468208, "acc_norm_stderr": 0.03242414757483098 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5392156862745098, "acc_stderr": 0.049598599663841815, "acc_norm": 0.5392156862745098, "acc_norm_stderr": 0.049598599663841815 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.03942772444036624, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036624 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7914893617021277, "acc_stderr": 0.026556982117838742, "acc_norm": 0.7914893617021277, "acc_norm_stderr": 0.026556982117838742 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5526315789473685, "acc_stderr": 0.04677473004491199, "acc_norm": 0.5526315789473685, "acc_norm_stderr": 0.04677473004491199 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7448275862068966, "acc_stderr": 0.03632984052707842, "acc_norm": 0.7448275862068966, "acc_norm_stderr": 0.03632984052707842 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6878306878306878, "acc_stderr": 0.023865206836972595, "acc_norm": 0.6878306878306878, "acc_norm_stderr": 0.023865206836972595 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5714285714285714, "acc_stderr": 0.0442626668137991, "acc_norm": 0.5714285714285714, "acc_norm_stderr": 0.0442626668137991 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8870967741935484, "acc_stderr": 0.01800360332586362, "acc_norm": 0.8870967741935484, "acc_norm_stderr": 0.01800360332586362 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5911330049261084, "acc_stderr": 0.034590588158832314, "acc_norm": 0.5911330049261084, "acc_norm_stderr": 0.034590588158832314 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8727272727272727, "acc_stderr": 0.02602465765165619, "acc_norm": 0.8727272727272727, "acc_norm_stderr": 0.02602465765165619 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9090909090909091, "acc_stderr": 0.020482086775424208, "acc_norm": 0.9090909090909091, "acc_norm_stderr": 0.020482086775424208 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9481865284974094, "acc_stderr": 0.01599622932024412, "acc_norm": 0.9481865284974094, "acc_norm_stderr": 0.01599622932024412 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8, "acc_stderr": 0.020280805062535726, "acc_norm": 0.8, "acc_norm_stderr": 0.020280805062535726 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.4777777777777778, "acc_stderr": 0.030455413985678408, "acc_norm": 0.4777777777777778, "acc_norm_stderr": 0.0304554139856