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fix full/freeze tuning for mllm

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Former-commit-id: 08564838bd
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hiyouga
2024-05-27 20:37:57 +08:00
parent 605e70d0e1
commit b88ecd71fd
7 changed files with 76 additions and 61 deletions
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16
src/llamafactory/hparams/finetuning_args.py
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@@ -311,6 +311,14 @@ class FinetuningArguments(FreezeArguments, LoraArguments, RLHFArguments, GaloreA
default=False,
metadata={"help": "Whether or not to make only the parameters in the expanded blocks trainable."},
)
freeze_vision_tower: bool = field(
default=True,
metadata={"help": "Whether ot not to freeze vision tower in MLLM training."},
)
train_mm_proj_only: bool = field(
default=False,
metadata={"help": "Whether or not to train the multimodal projector for MLLM only."},
)
plot_loss: bool = field(
default=False,
metadata={"help": "Whether or not to save the training loss curves."},
@@ -328,6 +336,7 @@ class FinetuningArguments(FreezeArguments, LoraArguments, RLHFArguments, GaloreA
self.lora_target = split_arg(self.lora_target)
self.additional_target = split_arg(self.additional_target)
self.galore_target = split_arg(self.galore_target)
self.freeze_vision_tower = self.freeze_vision_tower or self.train_mm_proj_only
assert self.finetuning_type in ["lora", "freeze", "full"], "Invalid fine-tuning method."
assert self.ref_model_quantization_bit in [None, 8, 4], "We only accept 4-bit or 8-bit quantization."
@@ -345,7 +354,7 @@ class FinetuningArguments(FreezeArguments, LoraArguments, RLHFArguments, GaloreA
raise ValueError("`dpo_label_smoothing` is only valid for sigmoid loss function.")
if self.use_llama_pro and self.finetuning_type == "full":
raise ValueError("`use_llama_pro` is only valid for the Freeze or LoRA training.")
raise ValueError("`use_llama_pro` is only valid for Freeze or LoRA training.")
if self.finetuning_type == "lora" and (self.use_galore or self.use_badam):
raise ValueError("Cannot use LoRA with GaLore or BAdam together.")
@@ -354,4 +363,7 @@ class FinetuningArguments(FreezeArguments, LoraArguments, RLHFArguments, GaloreA
raise ValueError("Cannot use GaLore with BAdam together.")
if self.loraplus_lr_ratio is not None and self.finetuning_type != "lora":
raise ValueError("`loraplus_lr_ratio` is only valid for the LoRA training.")
raise ValueError("`loraplus_lr_ratio` is only valid for LoRA training.")
if self.train_mm_proj_only and self.finetuning_type != "full":
raise ValueError("`train_mm_proj_only` is only valid for full training.")

4
src/llamafactory/hparams/model_args.py
View File

@@ -85,10 +85,6 @@ class ModelArguments:
default=False,
metadata={"help": "Whethor or not to use multimodal LLM that accepts visual inputs."},
)
tune_mm_proj: bool = field(
default=False,
metadata={"help": "Whethor or not only finetune mm_projector for MLLM."},
)
moe_aux_loss_coef: Optional[float] = field(
default=None,
metadata={"help": "Coefficient of the auxiliary router loss in mixture-of-experts model."},