open-llm-leaderboard-old/details_rombodawg__Open_Gpt4_8x7B_v0.2

该数据集是在模型 rombodawg/Open_Gpt4_8x7B_v0.2 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，每个配置对应一个被评估的任务。数据集包含 1 次运行的数据，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，还有一个名为 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 Hugging Face datasets 库加载数据集的示例。

原始信息汇总

数据集概述

该数据集是在对模型 rombodawg/Open_Gpt4_8x7B_v0.2 进行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拆分，拆分名称使用运行的时间戳。
• "train" 拆分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_rombodawg__Open_Gpt4_8x7B_v0.2", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-13T18:56:10.033721 运行的最新结果：

python { "all": { "acc": 0.7188157275221039, "acc_stderr": 0.030029707306740233, "acc_norm": 0.7225114431475408, "acc_norm_stderr": 0.03061684137993921, "mc1": 0.5605875152998776, "mc1_stderr": 0.017374520482513707, "mc2": 0.7191590734021742, "mc2_stderr": 0.014814881257041205 }, "harness|arc:challenge|25": { "acc": 0.6646757679180887, "acc_stderr": 0.01379618294778556, "acc_norm": 0.6868600682593856, "acc_norm_stderr": 0.013552671543623496 }, "harness|hellaswag|10": { "acc": 0.6761601274646485, "acc_stderr": 0.0046698341309770785, "acc_norm": 0.8615813582951604, "acc_norm_stderr": 0.0034463307489637123 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7407407407407407, "acc_stderr": 0.03785714465066653, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.03785714465066653 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8223684210526315, "acc_stderr": 0.031103182383123377, "acc_norm": 0.8223684210526315, "acc_norm_stderr": 0.031103182383123377 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.73, "acc_stderr": 0.0446196043338474, "acc_norm": 0.73, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7962264150943397, "acc_stderr": 0.024790784501775406, "acc_norm": 0.7962264150943397, "acc_norm_stderr": 0.024790784501775406 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8402777777777778, "acc_stderr": 0.030635578972093288, "acc_norm": 0.8402777777777778, "acc_norm_stderr": 0.030635578972093288 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7514450867052023, "acc_stderr": 0.03295304696818318, "acc_norm": 0.7514450867052023, "acc_norm_stderr": 0.03295304696818318 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5196078431372549, "acc_stderr": 0.04971358884367405, "acc_norm": 0.5196078431372549, "acc_norm_stderr": 0.04971358884367405 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.79, "acc_stderr": 0.04093601807403326, "acc_norm": 0.79, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.723404255319149, "acc_stderr": 0.02924188386962882, "acc_norm": 0.723404255319149, "acc_norm_stderr": 0.02924188386962882 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.631578947368421, "acc_stderr": 0.04537815354939391, "acc_norm": 0.631578947368421, "acc_norm_stderr": 0.04537815354939391 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6689655172413793, "acc_stderr": 0.03921545312467122, "acc_norm": 0.6689655172413793, "acc_norm_stderr": 0.03921545312467122 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.5317460317460317, "acc_stderr": 0.0256993528321318, "acc_norm": 0.5317460317460317, "acc_norm_stderr": 0.0256993528321318 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5317460317460317, "acc_stderr": 0.04463112720677173, "acc_norm": 0.5317460317460317, "acc_norm_stderr": 0.04463112720677173 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.864516129032258, "acc_stderr": 0.01946933458648693, "acc_norm": 0.864516129032258, "acc_norm_stderr": 0.01946933458648693 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6305418719211823, "acc_stderr": 0.03395970381998574, "acc_norm": 0.6305418719211823, "acc_norm_stderr": 0.03395970381998574 }, "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": 0.8121212121212121, "acc_stderr": 0.03050193405942914, "acc_norm": 0.8121212121212121, "acc_norm_stderr": 0.03050193405942914 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8686868686868687, "acc_stderr": 0.02406315641682253, "acc_norm": 0.8686868686868687, "acc_norm_stderr": 0.02406315641682253 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9378238341968912, "acc_stderr": 0.017426974154240524, "acc_norm": 0.9378238341968912, "acc_norm_stderr": 0.017426974154240524 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7205128205128205, "acc_stderr": 0.022752388839776823, "acc_norm": 0.7205128205128205, "acc_norm_stderr": 0.022752388839776823 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.36666666666666664, "acc_stderr": 0.02938162072646507, "acc_norm": 0.36666666666666664, "acc_norm_stderr": 0.02938162