fix: by hiyouga suggestion

Former-commit-id: 3a7ea2048a41eafc41fdca944e142f5a0f35a5b3

src/llamafactory/hparams/finetuning_args.py

@@ -308,10 +308,10 @@ class BAdamArgument:
 class SwanLabArguments:
     use_swanlab: bool = field(
         default=False,
-        metadata={"help": "Whether or not to use the SwanLab (an experiment tracking and visualization tools)."},
+        metadata={"help": "Whether or not to use the SwanLab (an experiment tracking and visualization tool)."},
     )
     swanlab_project: str = field(
-        default=None,
+        default="LLaMA Factory",
         metadata={"help": "The project name in SwanLab."},
     )
     swanlab_workspace: str = field(

src/llamafactory/train/dpo/trainer.py

@@ -31,7 +31,7 @@ from typing_extensions import override
 from ...extras.constants import IGNORE_INDEX
 from ...extras.packages import is_transformers_version_equal_to_4_46
 from ..callbacks import PissaConvertCallback, SaveProcessorCallback
-from ..trainer_utils import create_custom_optimizer, create_custom_scheduler, get_batch_logps
+from ..trainer_utils import create_custom_optimizer, create_custom_scheduler, get_batch_logps, get_swanlab_callback
 
 
 if TYPE_CHECKING:
@@ -106,6 +106,9 @@ class CustomDPOTrainer(DPOTrainer):
             self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
             self.add_callback(BAdamCallback)
 
+        if finetuning_args.use_swanlab:
+            self.add_callback(get_swanlab_callback(finetuning_args))
+
     @override
     def create_optimizer(self) -> "torch.optim.Optimizer":
         if self.optimizer is None:

src/llamafactory/train/kto/trainer.py

@@ -30,7 +30,7 @@ from typing_extensions import override
 from ...extras.constants import IGNORE_INDEX
 from ...extras.packages import is_transformers_version_equal_to_4_46
 from ..callbacks import SaveProcessorCallback
-from ..trainer_utils import create_custom_optimizer, create_custom_scheduler, get_batch_logps
+from ..trainer_utils import create_custom_optimizer, create_custom_scheduler, get_batch_logps, get_swanlab_callback
 
 
 if TYPE_CHECKING:
@@ -101,6 +101,9 @@ class CustomKTOTrainer(KTOTrainer):
             self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
             self.add_callback(BAdamCallback)
 
+        if finetuning_args.use_swanlab:
+            self.add_callback(get_swanlab_callback(finetuning_args))
+
     @override
     def create_optimizer(self) -> "torch.optim.Optimizer":
         if self.optimizer is None:

src/llamafactory/train/ppo/trainer.py

@@ -40,7 +40,7 @@ from typing_extensions import override
 from ...extras import logging
 from ...extras.misc import AverageMeter, count_parameters, get_current_device, get_logits_processor
 from ..callbacks import FixValueHeadModelCallback, SaveProcessorCallback
-from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
+from ..trainer_utils import create_custom_optimizer, create_custom_scheduler, get_swanlab_callback
 from .ppo_utils import dump_layernorm, get_rewards_from_server, replace_model, restore_layernorm
 
 
@@ -186,6 +186,9 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
             self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
             self.add_callback(BAdamCallback)
 
+        if finetuning_args.use_swanlab:
+            self.add_callback(get_swanlab_callback(finetuning_args))
+
     def ppo_train(self, resume_from_checkpoint: Optional[str] = None) -> None:
         r"""
         Implements training loop for the PPO stage, like _inner_training_loop() in Huggingface's Trainer.

src/llamafactory/train/pt/trainer.py

@@ -20,7 +20,7 @@ from typing_extensions import override
 
 from ...extras.packages import is_transformers_version_equal_to_4_46, is_transformers_version_greater_than
 from ..callbacks import PissaConvertCallback, SaveProcessorCallback
-from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
+from ..trainer_utils import create_custom_optimizer, create_custom_scheduler, get_swanlab_callback
 
 
 if TYPE_CHECKING:
@@ -56,6 +56,9 @@ class CustomTrainer(Trainer):
             self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
             self.add_callback(BAdamCallback)
 
+        if finetuning_args.use_swanlab:
+            self.add_callback(get_swanlab_callback(finetuning_args))
+
     @override
     def create_optimizer(self) -> "torch.optim.Optimizer":
         if self.optimizer is None:

src/llamafactory/train/rm/trainer.py

@@ -27,7 +27,7 @@ from typing_extensions import override
 from ...extras import logging
 from ...extras.packages import is_transformers_version_equal_to_4_46, is_transformers_version_greater_than
 from ..callbacks import FixValueHeadModelCallback, PissaConvertCallback, SaveProcessorCallback
-from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
+from ..trainer_utils import create_custom_optimizer, create_custom_scheduler, get_swanlab_callback
 
 
 if TYPE_CHECKING:
@@ -68,6 +68,9 @@ class PairwiseTrainer(Trainer):
             self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
             self.add_callback(BAdamCallback)
 
+        if finetuning_args.use_swanlab:
+            self.add_callback(get_swanlab_callback(finetuning_args))
+
     @override
     def create_optimizer(self) -> "torch.optim.Optimizer":
         if self.optimizer is None:

src/llamafactory/webui/locales.py

@@ -1438,7 +1438,7 @@ LOCALES = {
     },
     "swanlab_experiment_name": {
         "en": {
-            "label": "Experiment_name(optional)",
+            "label": "Experiment name (optional)",
         },
         "ru": {
             "label": "Имя эксперимента(Необязательный)",