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from dataclasses import dataclass, field
@dataclass
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"})
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