open-llm-leaderboard-old/details_nisten__shqiponja-59b-v1

该数据集是在模型nisten/shqiponja-59b-v1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。数据集包含1次运行的结果，每次运行在每个配置中表示为特定的分割，分割名称使用运行的时间戳。train分割始终指向最新的结果。此外，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Open LLM Leaderboard上的聚合指标。README还提供了如何使用`datasets`库中的`load_dataset`函数加载数据集的示例。

原始信息汇总

数据集概述

该数据集是在模型 nisten/shqiponja-59b-v1 的评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集组成

• 数据集包含 63 个配置，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。
• 额外的 "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_nisten__shqiponja-59b-v1", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-14T05:56:39.495831 运行 的最新结果： python { "all": { "acc": 0.7432378535506855, "acc_stderr": 0.02859899074099913, "acc_norm": 0.7559556232571321, "acc_norm_stderr": 0.029186017628606568, "mc1": 0.5373317013463892, "mc1_stderr": 0.017454645150970588, "mc2": 0.7043324455434049, "mc2_stderr": 0.014572093049489886 }, "harness|arc:challenge|25": { "acc": 0.6757679180887372, "acc_stderr": 0.01367881039951882, "acc_norm": 0.7005119453924915, "acc_norm_stderr": 0.01338502163731357 }, "harness|hellaswag|10": { "acc": 0.6440948018323043, "acc_stderr": 0.004778081784542404, "acc_norm": 0.8405696076478789, "acc_norm_stderr": 0.0036532880435558015 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.725925925925926, "acc_stderr": 0.03853254836552003, "acc_norm": 0.725925925925926, "acc_norm_stderr": 0.03853254836552003 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8552631578947368, "acc_stderr": 0.028631951845930387, "acc_norm": 0.8552631578947368, "acc_norm_stderr": 0.028631951845930387 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8075471698113208, "acc_stderr": 0.024262979839372274, "acc_norm": 0.8075471698113208, "acc_norm_stderr": 0.024262979839372274 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8819444444444444, "acc_stderr": 0.026983346503309382, "acc_norm": 0.8819444444444444, "acc_norm_stderr": 0.026983346503309382 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7341040462427746, "acc_stderr": 0.03368762932259431, "acc_norm": 0.7341040462427746, "acc_norm_stderr": 0.03368762932259431 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5196078431372549, "acc_stderr": 0.04971358884367406, "acc_norm": 0.5196078431372549, "acc_norm_stderr": 0.04971358884367406 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7659574468085106, "acc_stderr": 0.027678452578212394, "acc_norm": 0.7659574468085106, "acc_norm_stderr": 0.027678452578212394 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5964912280701754, "acc_stderr": 0.04615186962583707, "acc_norm": 0.5964912280701754, "acc_norm_stderr": 0.04615186962583707 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7034482758620689, "acc_stderr": 0.03806142687309992, "acc_norm": 0.7034482758620689, "acc_norm_stderr": 0.03806142687309992 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.5846560846560847, "acc_stderr": 0.0253795249107784, "acc_norm": 0.5846560846560847, "acc_norm_stderr": 0.0253795249107784 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.6031746031746031, "acc_stderr": 0.0437588849272706, "acc_norm": 0.6031746031746031, "acc_norm_stderr": 0.0437588849272706 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.9, "acc_stderr": 0.01706640371965727, "acc_norm": 0.9, "acc_norm_stderr": 0.01706640371965727 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6551724137931034, "acc_stderr": 0.03344283744280458, "acc_norm": 0.6551724137931034, "acc_norm_stderr": 0.03344283744280458 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.76, "acc_stderr": 0.04292346959909282, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909282 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8666666666666667, "acc_stderr": 0.026544435312706463, "acc_norm": 0.8666666666666667, "acc_norm_stderr": 0.026544435312706463 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9242424242424242, "acc_stderr": 0.018852670234993093, "acc_norm": 0.9242424242424242, "acc_norm_stderr": 0.018852670234993093 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9585492227979274, "acc_stderr": 0.014385432857476444, "acc_norm": 0.9585492227979274, "acc_norm_stderr": 0.014385432857476444 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8076923076923077, "acc_stderr": 0.0199823472086373, "acc_norm": 0.8076923076923077, "acc_norm_stderr": 0.0199823472086373 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3888888888888889, "acc_stderr": 0.029723278961476668, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.029723278961476668 }, "harness|hendrycksTest-high_