open-llm-leaderboard/details_ajibawa-2023__Uncensored-Jordan-13B

该数据集是在评估模型ajibawa-2023/Uncensored-Jordan-13B时自动创建的，用于在Open LLM Leaderboard上进行评估。数据集包含64个配置，每个配置对应一个评估任务。数据集由1次运行生成，每次运行的结果可以在每个配置的特定分割中找到，分割名称使用运行的时间戳命名。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

该数据集是在评估模型 ajibawa-2023/Uncensored-Jordan-13B 在 Open LLM Leaderboard 上的运行过程中自动创建的。

数据集组成

• 该数据集包含 64 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，每个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_ajibawa-2023__Uncensored-Jordan-13B_public", "harness_winogrande_5", split="train")

最新结果

以下是 2023-11-18T18:01:22.350849 运行的最新结果：

python { "all": { "acc": 0.5551346436733366, "acc_stderr": 0.033773935379363566, "acc_norm": 0.5623156588862028, "acc_norm_stderr": 0.03452935511879212, "mc1": 0.35006119951040393, "mc1_stderr": 0.01669794942015103, "mc2": 0.5051246541228124, "mc2_stderr": 0.015683474268697605, "em": 0.10371224832214765, "em_stderr": 0.003122327158910168, "f1": 0.1647325922818787, "f1_stderr": 0.003269141000174996 }, "harness|arc:challenge|25": { "acc": 0.5401023890784983, "acc_stderr": 0.014564318856924848, "acc_norm": 0.5742320819112628, "acc_norm_stderr": 0.01444946427886881 }, "harness|hellaswag|10": { "acc": 0.6352320254929297, "acc_stderr": 0.004803812631994952, "acc_norm": 0.8270264887472615, "acc_norm_stderr": 0.0037745138826159514 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5657894736842105, "acc_stderr": 0.04033565667848319, "acc_norm": 0.5657894736842105, "acc_norm_stderr": 0.04033565667848319 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6075471698113207, "acc_stderr": 0.03005258057955785, "acc_norm": 0.6075471698113207, "acc_norm_stderr": 0.03005258057955785 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5833333333333334, "acc_stderr": 0.041227287076512825, "acc_norm": 0.5833333333333334, "acc_norm_stderr": 0.041227287076512825 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5317919075144508, "acc_stderr": 0.03804749744364764, "acc_norm": 0.5317919075144508, "acc_norm_stderr": 0.03804749744364764 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201942, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201942 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4851063829787234, "acc_stderr": 0.032671518489247764, "acc_norm": 0.4851063829787234, "acc_norm_stderr": 0.032671518489247764 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.21929824561403508, "acc_stderr": 0.03892431106518754, "acc_norm": 0.21929824561403508, "acc_norm_stderr": 0.03892431106518754 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.31746031746031744, "acc_stderr": 0.023973861998992065, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.023973861998992065 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.373015873015873, "acc_stderr": 0.043255060420170854, "acc_norm": 0.373015873015873, "acc_norm_stderr": 0.043255060420170854 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6516129032258065, "acc_stderr": 0.027104826328100944, "acc_norm": 0.6516129032258065, "acc_norm_stderr": 0.027104826328100944 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.41379310344827586, "acc_stderr": 0.03465304488406795, "acc_norm": 0.41379310344827586, "acc_norm_stderr": 0.03465304488406795 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6727272727272727, "acc_stderr": 0.03663974994391244, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.03663974994391244 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6919191919191919, "acc_stderr": 0.032894773300986155, "acc_norm": 0.6919191919191919, "acc_norm_stderr": 0.032894773300986155 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8031088082901554, "acc_stderr": 0.028697873971860688, "acc_norm": 0.8031088082901554, "acc_norm_stderr": 0.028697873971860688 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4897435897435897, "acc_stderr": 0.025345672221942374, "acc_norm": 0.4897435897435897, "acc_norm_stderr": 0