ainewtrend07/T

该数据集包含模型的名称、训练集和测试集的大小、超参数设置等信息。具体包括梯度积累步数、学习率、日志记录步数、学习率调度器类型、训练周期数、优化器类型、输出目录、每个设备的训练批量大小、报告目标、随机种子、预热步数、权重衰减等。此外，还包含LoRA参数列表、总参数数量、可训练参数数量、内存分配情况、训练时间以及性能指标（如准确率、F1宏平均值、F1加权平均值、精确度、召回率等）。

The dataset includes model name, train and test set sizes, hyperparameter settings, and other information. Specifically, it includes gradient accumulation steps, learning rate, logging steps, learning rate scheduler type, number of training epochs, optimizer type, output directory, per-device training batch size, reporting target, random seed, warmup steps, weight decay, LoRA parameter list, total number of parameters, trainable parameters, memory allocation, training time, and performance metrics (such as accuracy, F1 macro, F1 weighted, precision, recall, etc.).