ainewtrend07/EncoderLora

该数据集包含了模型训练和评估所需的多种参数和性能指标，如模型名称、训练集和测试集大小、是否自动寻找批处理大小、梯度累积步数、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、报告输出位置、保存策略、保存限制、随机种子、预热步数、权重衰减、LoRA序列、参数数量、可训练参数数量、相关系数、内存分配和训练时间等。此外，数据集的性能指标包括准确率、宏平均F1分数、加权平均F1分数、精确率、召回率等。训练集包含了19个示例，总字节数为5144字节。

The dataset includes various parameters and performance metrics necessary for model training and evaluation, such as model name, training and test set sizes, whether to automatically find batch size, gradient accumulation steps, learning rate, logging steps, learning rate scheduler type, number of training epochs, optimizer type, output directory, reporting output location, save strategy, save total limit, random seed, warmup steps, weight decay, LoRA sequence, number of parameters, number of trainable parameters, correlation coefficient, memory allocation, training time, etc. Additionally, the datasets performance metrics include accuracy, macro F1 score, weighted F1 score, precision, recall, etc. The training set contains 19 examples with a total of 5144 bytes.