in peft finetune, only the trainable parameters need to be saved

to reduce the storage size and also save the time of checkpoint saving while using deepspeed for training

Signed-off-by: Wang, Yi <[email protected]>

src/transformers/trainer.py

@@ -2419,7 +2419,13 @@ def _save_optimizer_and_scheduler(self, output_dir):
         elif self.is_deepspeed_enabled:
             # under zero3 model file itself doesn't get saved since it's bogus! Unless deepspeed
             # config `stage3_gather_16bit_weights_on_model_save` is True
-            self.model_wrapped.save_checkpoint(output_dir)
+            accept_exclude_frozen_parameters = "exclude_frozen_parameters" in set(
+                inspect.signature(self.model_wrapped.save_checkpoint).parameters.keys()
+            )
+            if accept_exclude_frozen_parameters and is_peft_available() and isinstance(self.model, PeftModel):
+                self.model_wrapped.save_checkpoint(output_dir, exclude_frozen_parameters=True)
+            else:
+                self.model_wrapped.save_checkpoint(output_dir)
         elif self.is_fsdp_enabled:
             # save fsdp specific ckpt for resuming from ckpt
             save_fsdp_model(self.accelerator.state.fsdp_plugin, self.accelerator, self.model, output_dir)