open-llm-leaderboard-old/details_yunconglong__7Bx4_DPO_2e

该数据集是在模型yunconglong/7Bx4_DPO_2e在Open LLM Leaderboard上的评估过程中自动生成的。数据集由63个配置组成，每个配置对应一个评估任务。它包含一次运行的结果，每次运行作为每个配置中的一个特定分割存储，分割名称由运行的时间戳命名。train分割始终指向最新的结果。此外，还有一个results配置，用于汇总所有运行结果，并用于计算和显示Open LLM Leaderboard上的指标。文件还提供了如何使用Hugging Face datasets库加载数据集的示例。

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 yunconglong/7Bx4_DPO_2e 在 Open LLM Leaderboard 上的运行过程中自动创建的。数据集包含 63 个配置，每个配置对应一个评估任务。

数据集结构

• 配置数量：63 个配置
• 数据来源：从 1 次运行中创建
• 数据分割：每个配置包含特定分割，分割名称使用运行的时间戳。"train" 分割始终指向最新结果。
• 额外配置："results" 配置存储所有运行的聚合结果，用于计算和显示聚合指标在 Open LLM Leaderboard 上。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_yunconglong__7Bx4_DPO_2e", "harness_winogrande_5", split="train")

最新结果

这些是最新结果，来自 2024-01-20T07:53:49.728301 的运行： python { "all": { "acc": 0.6497382445744926, "acc_stderr": 0.032094653254152825, "acc_norm": 0.6495590967657305, "acc_norm_stderr": 0.03275779052761359, "mc1": 0.5030599755201959, "mc1_stderr": 0.01750317326096063, "mc2": 0.6560145251092138, "mc2_stderr": 0.014910139553633708 }, "harness|arc:challenge|25": { "acc": 0.6672354948805461, "acc_stderr": 0.013769863046192309, "acc_norm": 0.689419795221843, "acc_norm_stderr": 0.013522292098053067 }, "harness|hellaswag|10": { "acc": 0.6793467436765585, "acc_stderr": 0.004657738398900936, "acc_norm": 0.8679545907189803, "acc_norm_stderr": 0.003378482488748873 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.26, "acc_stderr": 0.044084400227680794, "acc_norm": 0.26, "acc_norm_stderr": 0.044084400227680794 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6444444444444445, "acc_stderr": 0.04135176749720385, "acc_norm": 0.6444444444444445, "acc_norm_stderr": 0.04135176749720385 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6907894736842105, "acc_stderr": 0.037610708698674805, "acc_norm": 0.6907894736842105, "acc_norm_stderr": 0.037610708698674805 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7018867924528301, "acc_stderr": 0.02815283794249387, "acc_norm": 0.7018867924528301, "acc_norm_stderr": 0.02815283794249387 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7708333333333334, "acc_stderr": 0.03514697467862388, "acc_norm": 0.7708333333333334, "acc_norm_stderr": 0.03514697467862388 }, "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": 0.56, "acc_stderr": 0.049888765156985884, "acc_norm": 0.56, "acc_norm_stderr": 0.049888765156985884 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.43137254901960786, "acc_stderr": 0.04928099597287534, "acc_norm": 0.43137254901960786, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.04292346959909283, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5957446808510638, "acc_stderr": 0.03208115750788684, "acc_norm": 0.5957446808510638, "acc_norm_stderr": 0.03208115750788684 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5379310344827586, "acc_stderr": 0.04154659671707548, "acc_norm": 0.5379310344827586, "acc_norm_stderr": 0.04154659671707548 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086924003, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086924003 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4365079365079365, "acc_stderr": 0.04435932892851466, "acc_norm": 0.4365079365079365, "acc_norm_stderr": 0.04435932892851466 }, "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": 0.7741935483870968, "acc_stderr": 0.023785577884181015, "acc_norm": 0.7741935483870968, "acc_norm_stderr": 0.023785577884181015 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.47783251231527096, "acc_stderr": 0.03514528562175008, "acc_norm": 0.47783251231527096, "acc_norm_stderr": 0.03514528562175008 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7757575757575758, "acc_stderr": 0.03256866661681102, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.03256866661681102 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7878787878787878, "acc_stderr": 0.029126522834586815, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.029126522834586815 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8808290155440415, "acc_stderr": 0.023381935348121434, "acc_norm": 0.8808290155440415, "acc_norm_stderr": 0.023381935348121434 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.658974358974359, "acc_stderr": 0.024035489676335075, "acc_norm": 0.658974358974359, "acc_norm_stderr": 0.024035489676335075 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.028742040903948485, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.028742040903948485 }, "harness|hendrycksTest-high_school_microeconomics