open-llm-leaderboard-old/details_ALBADDAWI__DeepCode-7B-Aurora-v3

该数据集是在评估模型ALBADDAWI/DeepCode-7B-Aurora-v3时自动创建的，评估是在Open LLM Leaderboard上进行的。数据集由63个配置组成，每个配置对应一个评估任务。数据集是从1次运行中创建的，每次运行可以在每个配置中找到，分割名称使用运行的时间戳。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，并用于计算和显示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

该数据集是在对模型 ALBADDAWI/DeepCode-7B-Aurora-v3 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

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。
• 运行次数：数据集从1次运行中创建。每个运行在每个配置中作为一个特定的分割存在，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："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_ALBADDAWI__DeepCode-7B-Aurora-v3", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-11T05:19:07.214398 运行的最新结果：

python { "all": { "acc": 0.5681495136207636, "acc_stderr": 0.03451590964955344, "acc_norm": 0.5751358564434681, "acc_norm_stderr": 0.03524650761892643, "mc1": 0.29498164014687883, "mc1_stderr": 0.015964400965589667, "mc2": 0.4065312575872176, "mc2_stderr": 0.01505222686802986 }, "harness|arc:challenge|25": { "acc": 0.5179180887372014, "acc_stderr": 0.014602005585490973, "acc_norm": 0.5460750853242321, "acc_norm_stderr": 0.01454922110517187 }, "harness|hellaswag|10": { "acc": 0.5433180641306513, "acc_stderr": 0.00497101994272659, "acc_norm": 0.7202748456482773, "acc_norm_stderr": 0.004479467619464795 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4074074074074074, "acc_stderr": 0.04244633238353227, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.04244633238353227 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6447368421052632, "acc_stderr": 0.03894734487013317, "acc_norm": 0.6447368421052632, "acc_norm_stderr": 0.03894734487013317 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.569811320754717, "acc_stderr": 0.030471445867183235, "acc_norm": 0.569811320754717, "acc_norm_stderr": 0.030471445867183235 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5902777777777778, "acc_stderr": 0.04112490974670787, "acc_norm": 0.5902777777777778, "acc_norm_stderr": 0.04112490974670787 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5606936416184971, "acc_stderr": 0.037842719328874674, "acc_norm": 0.5606936416184971, "acc_norm_stderr": 0.037842719328874674 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.43137254901960786, "acc_stderr": 0.04928099597287533, "acc_norm": 0.43137254901960786, "acc_norm_stderr": 0.04928099597287533 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6468085106382979, "acc_stderr": 0.031245325202761926, "acc_norm": 0.6468085106382979, "acc_norm_stderr": 0.031245325202761926 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.04702880432049615, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.04702880432049615 }, "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": 0.5846560846560847, "acc_stderr": 0.025379524910778387, "acc_norm": 0.5846560846560847, "acc_norm_stderr": 0.025379524910778387 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5396825396825397, "acc_stderr": 0.04458029125470973, "acc_norm": 0.5396825396825397, "acc_norm_stderr": 0.04458029125470973 }, "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": 0.6483870967741936, "acc_stderr": 0.02716253782694846, "acc_norm": 0.6483870967741936, "acc_norm_stderr": 0.02716253782694846 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5467980295566502, "acc_stderr": 0.03502544650845872, "acc_norm": 0.5467980295566502, "acc_norm_stderr": 0.03502544650845872 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.73, "acc_stderr": 0.044619604333847394, "acc_norm": 0.73, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6787878787878788, "acc_stderr": 0.0364620496325381, "acc_norm": 0.6787878787878788, "acc_norm_stderr": 0.0364620496325381 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6919191919191919, "acc_stderr": 0.03289477330098616, "acc_norm": 0.6919191919191919, "acc_norm_stderr": 0.03289477330098616 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6787564766839378, "acc_stderr": 0.033699508685490674, "acc_norm": 0.6787564766839378, "acc_norm_stderr": 0.033699508685490674 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5948717948717949, "acc_stderr": 0.024890471769938145, "acc_norm": 0.5948717948717949, "acc_norm_stderr": 0.024890471769938145 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.42962962962962964, "acc_stderr": 0.030182099804387262, "acc_norm": 0.4296296