Fix step shifting when accumulate gradient

src/transformers/trainer.py

@@ -2404,7 +2404,6 @@ def _inner_training_loop(
         if args.eval_on_start:
             self._evaluate(trial, ignore_keys_for_eval, skip_scheduler=True)
 
-        total_batched_samples = 0
         for epoch in range(epochs_trained, num_train_epochs):
             epoch_dataloader = train_dataloader
             if hasattr(epoch_dataloader, "set_epoch"):
@@ -2447,13 +2446,7 @@ def _inner_training_loop(
                 batch_samples, num_items_in_batch = self.get_batch_samples(epoch_iterator, num_batches)
                 for inputs in batch_samples:
                     step += 1
-                    total_batched_samples += 1
-                    is_last_step_and_steps_less_than_grad_acc = (
-                        steps_in_epoch <= args.gradient_accumulation_steps and (step + 1) == steps_in_epoch
-                    )
-                    do_sync_step = is_last_step_and_steps_less_than_grad_acc or (
-                        total_batched_samples % args.gradient_accumulation_steps == 0
-                    )
+                    do_sync_step = (step + 1) % args.gradient_accumulation_steps == 0 or (step + 1) == steps_in_epoch
                     # Since we perform prefetching, we need to manually set sync_gradients
                     if not do_sync_step:
                         self.accelerator.gradient_state._set_sync_gradients(False)