Update all no_trainer with skip_first_batches (#23664)

examples/pytorch/token-classification/run_ner_no_trainer.py

@@ -668,12 +668,12 @@ def main():
         model.train()
         if args.with_tracking:
             total_loss = 0
-        for step, batch in enumerate(train_dataloader):
-            # We need to skip steps until we reach the resumed step
-            if args.resume_from_checkpoint and epoch == starting_epoch:
-                if resume_step is not None and step < resume_step:
-                    completed_steps += 1
-                    continue
+        if args.resume_from_checkpoint and epoch == starting_epoch and resume_step is not None:
+            # We skip the first `n` batches in the dataloader when resuming from a checkpoint
+            active_dataloader = accelerator.skip_first_batches(train_dataloader, resume_step)
+        else:
+            active_dataloader = train_dataloader
+        for step, batch in enumerate(active_dataloader):
             outputs = model(**batch)
             loss = outputs.loss
             # We keep track of the loss at each epoch