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fix #6448

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hiyouga
2024-12-27 16:54:39 +00:00
parent f68074d87b
commit 2719867982
7 changed files with 29 additions and 27 deletions
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10
src/llamafactory/train/kto/trainer.py
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@@ -77,6 +77,7 @@ class CustomKTOTrainer(KTOTrainer):
self.ftx_gamma = finetuning_args.pref_ftx
Trainer.__init__(self, model=model, **kwargs)
self.model_accepts_loss_kwargs = False # overwrite trainer's default behavior
if not hasattr(self, "accelerator"):
raise AttributeError("Please update `transformers`.")
@@ -252,15 +253,14 @@ class CustomKTOTrainer(KTOTrainer):
self, model: "PreTrainedModel", inputs: Dict[str, "torch.Tensor"], return_outputs: bool = False, **kwargs
) -> Union["torch.Tensor", Tuple["torch.Tensor", List["torch.Tensor"]]]:
r"""
Fixes the loss value for transformers 4.46.0.
https://github.com/huggingface/transformers/blob/v4.46.0/src/transformers/trainer.py#L3605
Fixes the loss value. See https://github.com/huggingface/transformers/pull/35438 for details.
"""
loss = super().compute_loss(model, inputs, return_outputs)
if is_transformers_version_equal_to_4_46() and kwargs.pop("num_items_in_batch", False):
if is_transformers_version_equal_to_4_46() and kwargs.get("num_items_in_batch"):
if return_outputs:
return (loss[0] / self.args.gradient_accumulation_steps, *loss[1:])
loss = (loss[0] / self.args.gradient_accumulation_steps, *loss[1:])
else:
return loss / self.args.gradient_accumulation_steps
loss = loss / self.args.gradient_accumulation_steps
return loss