args.py

import torch
class Config(object):

    """配置参数"""
    def __init__(self):
        self.model_name = 'Transformer'
        self.embedding_pretrained = None                                 # 预训练词向量
        self.device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')   # 设备
        self.dropout = 0.5                                              # 随机失活
        self.num_classes = 14                        # 类别数
        self.num_epochs = 20                                            # epoch数
        self.batch_size = 128                                           # mini-batch大小
        self.pad_size = 256                                              # 每句话处理成的长度(短填长切)
        self.n_vocab = None#这里需要读取数据的部分进行赋值
        self.learning_rate = 5e-4                                       # 学习率
        self.embed = 300           # 词向量维度
        self.dim_model = 300
        self.hidden = 1024
        self.last_hidden = 512
        self.num_head = 5
        self.num_encoder = 2
        self.n_splits = 5#k折交叉验证