open-llm-leaderboard/details_kajdun__iubaris-13b-v3

该数据集是在模型 kajdun/iubaris-13b-v3 在 Open LLM Leaderboard 上的评估过程中自动生成的。数据集包含 61 个配置，每个配置对应一个被评估的任务。数据集包含一次运行的结果，每次运行在每个配置中表示为特定的分割。train 分割始终指向最新的结果。一个名为 results 的额外配置存储了所有运行的聚合结果，这些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 Python 中的 datasets 库加载运行细节的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 kajdun/iubaris-13b-v3 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 61 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，每次运行的详细信息存储在特定的分割中，分割名称使用运行的时间戳。
• "train" 分割始终指向最新的结果。
• 一个额外的配置 "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_kajdun__iubaris-13b-v3", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是 2023-08-26T10:44:57.625308 运行的最新结果：

python { "all": { "acc": 0.5457651905991454, "acc_stderr": 0.03462957237621476, "acc_norm": 0.5496206901026076, "acc_norm_stderr": 0.03461040607243729, "mc1": 0.3402692778457772, "mc1_stderr": 0.016586304901762564, "mc2": 0.4860621835708466, "mc2_stderr": 0.015429990225329837 }, "harness|arc:challenge|25": { "acc": 0.5563139931740614, "acc_stderr": 0.014518421825670456, "acc_norm": 0.591296928327645, "acc_norm_stderr": 0.014365750345427 }, "harness|hellaswag|10": { "acc": 0.625273849830711, "acc_stderr": 0.004830628620181031, "acc_norm": 0.8177653853813981, "acc_norm_stderr": 0.003852488177553968 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5111111111111111, "acc_stderr": 0.04318275491977976, "acc_norm": 0.5111111111111111, "acc_norm_stderr": 0.04318275491977976 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5855263157894737, "acc_stderr": 0.04008973785779206, "acc_norm": 0.5855263157894737, "acc_norm_stderr": 0.04008973785779206 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.52, "acc_stderr": 0.05021167315686779, "acc_norm": 0.52, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6037735849056604, "acc_stderr": 0.030102793781791197, "acc_norm": 0.6037735849056604, "acc_norm_stderr": 0.030102793781791197 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5555555555555556, "acc_stderr": 0.041553199555931467, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.041553199555931467 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.48, "acc_stderr": 0.05021167315686779, "acc_norm": 0.48, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5028901734104047, "acc_stderr": 0.038124005659748335, "acc_norm": 0.5028901734104047, "acc_norm_stderr": 0.038124005659748335 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.27450980392156865, "acc_stderr": 0.04440521906179328, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.04440521906179328 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4127659574468085, "acc_stderr": 0.03218471141400351, "acc_norm": 0.4127659574468085, "acc_norm_stderr": 0.03218471141400351 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2631578947368421, "acc_stderr": 0.041424397194893624, "acc_norm": 0.2631578947368421, "acc_norm_stderr": 0.041424397194893624 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4689655172413793, "acc_stderr": 0.04158632762097828, "acc_norm": 0.4689655172413793, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3412698412698413, "acc_stderr": 0.024419234966819064, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.024419234966819064 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.36507936507936506, "acc_stderr": 0.04306241259127153, "acc_norm": 0.36507936507936506, "acc_norm_stderr": 0.04306241259127153 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6451612903225806, "acc_stderr": 0.02721888977330877, "acc_norm": 0.6451612903225806, "acc_norm_stderr": 0.02721888977330877 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4433497536945813, "acc_stderr": 0.03495334582162934, "acc_norm": 0.4433497536945813, "acc_norm_stderr": 0.03495334582162934 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145633, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6545454545454545, "acc_stderr": 0.037131580674819135, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.037131580674819135 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6868686868686869, "acc_stderr": 0.033042050878136525, "acc_norm": 0.6868686868686869, "acc_norm_stderr": 0.033042050878136525 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7875647668393783, "acc_stderr": 0.029519282616817234, "acc_norm": 0.7875647668393783, "acc_norm_stderr": 0.029519282616817234 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5205128205128206, "acc_stderr": 0.02532966316348994, "acc_norm": 0.5205128205128206, "acc_norm_stderr": 0.02532966316348994 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3, "acc_stderr": 0.02794045713622842, "acc_norm": 0.3, "acc_norm_stderr": 0.02794045713622842 },