| from dataclasses import dataclass, field | |
| class CaptionArguments: | |
| """ | |
| 自定义的一些参数 | |
| Arguments pertaining to which model/config/tokenizer we are going to fine-tune from. | |
| """ | |
| max_seq_length: int = field(metadata={"help": "输入最大长度"}) | |
| train_caption_file: str = field(metadata={"help": "训练集"}) | |
| train_image_file: str = field(metadata={"help": "训练集"}) | |
| test_caption_file: str = field(metadata={"help": "测试集"}) | |
| test_image_file: str = field(metadata={"help": "测试集"}) | |
| model_name_or_path: str = field(metadata={"help": "预训练权重路径"}) | |
| freeze_encoder: bool = field(metadata={"help": "是否将encoder的权重冻结,仅对decoder进行finetune"}) | |
| freeze_word_embed: bool = field( | |
| metadata={"help": "是否将encoder的词向量的权重冻结,由于OFA模型的enocder与decoder共享词向量权重,所以freeze_encoder会将词向量冻结。当freeze_word_embed=False时,词向量会一起训练"}) | |