| from dataclasses import dataclass, field |
| from typing import Optional |
|
|
|
|
| @dataclass |
| class CoTArguments: |
| r""" |
| CoT embedding 训练特有的参数，与 utils.arguments 中已有的参数类配合使用。 |
| """ |
| infonce_weight: Optional[float] = field( |
| default=1.0, |
| metadata={"help": "weight of the embedding infonce loss"}, |
| ) |
| cot_weight: Optional[float] = field( |
| default=1.0, |
| metadata={"help": "weight of the cot cross entropy loss"}, |
| ) |
| max_cot_length: Optional[int] = field( |
| default=192, |
| metadata={"help": "max token length of the cot text, longer cot will be truncated"}, |
| ) |
| cot_emb_suffix: Optional[str] = field( |
| default="<|im_end|>", |
| metadata={"help": "suffix appended after the cot text, its hidden state is pooled as query embedding"}, |
| ) |
| doc_append_eos: Optional[bool] = field( |
| default=False, |
| metadata={"help": "also append cot_emb_suffix to doc side so that query/doc pool on the same token"}, |
| ) |
| train_lm_head: Optional[bool] = field( |
| default=False, |
| metadata={ |
| "help": "whether to finetune lm_head. lm_head is weight-tied with embed_tokens: " |
| "under full finetuning both are unfrozen/frozen together; " |
| "under LoRA a decoupled copy of lm_head is trained via modules_to_save " |
| "while embed_tokens stays frozen" |
| }, |
| ) |
| query_image_type: Optional[str] = field( |
| default=None, |
| metadata={"help": "image type of query side: full / crop / both. fall back to data_args.image_type"}, |
| ) |
| doc_image_type: Optional[str] = field( |
| default=None, |
| metadata={"help": "image type of doc side: full / crop / both. fall back to data_args.image_type"}, |
| ) |
|
|
| |
| |
| |
| use_wandb: Optional[bool] = field( |
| default=False, |
| metadata={"help": "enable wandb logging"}, |
| ) |
| wandb_api_key: Optional[str] = field( |
| default="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", |
| metadata={"help": "wandb login api key"}, |
| ) |
| wandb_project: Optional[str] = field( |
| default="cot_embedding", |
| metadata={"help": "wandb project name"}, |
| ) |
| wandb_entity: Optional[str] = field( |
| default="", |
| metadata={"help": "wandb entity (team or username), optional"}, |
| ) |
| wandb_run_name: Optional[str] = field( |
| default="lora_alpha128_train_head_local", |
| metadata={"help": "wandb run name, fall back to training_args.run_name"}, |
| ) |
| wandb_mode: Optional[str] = field( |
| default="online", |
| metadata={"help": "wandb mode: online / offline, use offline when workers have no internet access"}, |
| ) |
|
|
