Enable Gradient Accumulation fix across all models + trainer fully in forward() #34283
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@ArthurZucker |
man-shar
reviewed
Oct 22, 2024
| @@ -3610,8 +3612,11 @@ def compute_loss(self, model, inputs, return_outputs=False, num_items_in_batch=N | |||
| labels = inputs.pop("labels") | |||
| else: | |||
| labels = None | |||
| # if num_items_in_batch is not None: | |||
| # inputs["num_items_in_batch"] = num_items_in_batch | |||
| if self.model_accepts_loss_kwargs: | |||
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This if condition doesn't seem to work for PeftModel class (it only has kwargs not loss_kwargs 🫠 )
I tried just changing that condition to if True and ran some tests, and the loss calculation worked perfectly for a LORA on a Llama 3 1B.
I'm wondering if there's a safe/non-breaking way to support peft models here as well?
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Awesome work by all of you on this. Insane dev speed over the past few days 🙏 🔥 |
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What does this PR do?
Since most users still want OOTB, this trickles the loss kwargs to the rest of the models so that causal loss can be calculated properly
Fixes # (issue)
Fully fixes #34263 / finishes #34191 & #34198
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@ArthurZucker