open-llm-leaderboard-old/details_mahiatlinux__MasherAI-7B-v6.1

该数据集是在模型 mahiatlinux/MasherAI-7B-v6.1 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。它包含 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。train 分割始终指向最新的结果。此外，还有一个 results 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 库加载运行详情的示例。

原始信息汇总

数据集概述

数据集摘要

该数据集是在评估模型 mahiatlinux/MasherAI-7B-v6.1 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
• 创建来源：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。
• 特殊配置："results" 配置存储所有运行的聚合结果，用于计算和显示在 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_mahiatlinux__MasherAI-7B-v6.1", "harness_winogrande_5", split="train")

最新结果

这些是最新结果，来自 2024-04-21T08:39:55.419651 的运行： python { "all": { "acc": 0.6392078223145096, "acc_stderr": 0.03238370365947275, "acc_norm": 0.6401900676842683, "acc_norm_stderr": 0.03304925448351338, "mc1": 0.3684210526315789, "mc1_stderr": 0.016886551261046046, "mc2": 0.5547759456535772, "mc2_stderr": 0.015284052296808036 }, "harness|arc:challenge|25": { "acc": 0.6023890784982935, "acc_stderr": 0.014301752223279542, "acc_norm": 0.643344709897611, "acc_norm_stderr": 0.01399805690262019 }, "harness|hellaswag|10": { "acc": 0.6415056761601274, "acc_stderr": 0.00478578197935487, "acc_norm": 0.842162915753834, "acc_norm_stderr": 0.0036384306206139307 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6, "acc_stderr": 0.042320736951515885, "acc_norm": 0.6, "acc_norm_stderr": 0.042320736951515885 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6842105263157895, "acc_stderr": 0.0378272898086547, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.0378272898086547 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6792452830188679, "acc_stderr": 0.028727502957880267, "acc_norm": 0.6792452830188679, "acc_norm_stderr": 0.028727502957880267 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7013888888888888, "acc_stderr": 0.03827052357950756, "acc_norm": 0.7013888888888888, "acc_norm_stderr": 0.03827052357950756 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6358381502890174, "acc_stderr": 0.03669072477416907, "acc_norm": 0.6358381502890174, "acc_norm_stderr": 0.03669072477416907 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4411764705882353, "acc_stderr": 0.04940635630605659, "acc_norm": 0.4411764705882353, "acc_norm_stderr": 0.04940635630605659 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4298245614035088, "acc_stderr": 0.046570472605949625, "acc_norm": 0.4298245614035088, "acc_norm_stderr": 0.046570472605949625 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555497, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555497 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4365079365079365, "acc_stderr": 0.025542846817400502, "acc_norm": 0.4365079365079365, "acc_norm_stderr": 0.025542846817400502 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.47619047619047616, "acc_stderr": 0.04467062628403273, "acc_norm": 0.47619047619047616, "acc_norm_stderr": 0.04467062628403273 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7806451612903226, "acc_stderr": 0.023540799358723292, "acc_norm": 0.7806451612903226, "acc_norm_stderr": 0.023540799358723292 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4876847290640394, "acc_stderr": 0.035169204442208966, "acc_norm": 0.4876847290640394, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7515151515151515, "acc_stderr": 0.033744026441394036, "acc_norm": 0.7515151515151515, "acc_norm_stderr": 0.033744026441394036 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.803030303030303, "acc_stderr": 0.02833560973246336, "acc_norm": 0.803030303030303, "acc_norm_stderr": 0.02833560973246336 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8652849740932642, "acc_stderr": 0.02463978909770944, "acc_norm": 0.8652849740932642, "acc_norm_stderr": 0.02463978909770944 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6487179487179487, "acc_stderr": 0.024203665177902803, "acc_norm": 0.6487179487179487, "acc_norm_stderr": 0.024203665177902803 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32592592592592595, "acc_stderr": 0.028578348365473075, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.028578348365473075 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6470588235294118, "acc_stderr": 0.03104194130405