Split checkpoint from model_name_or_path in examples (#11492)

* Split checkpoint from model_name_or_path in examples

* Address review comments

* Address review comments

examples/pytorch/language-modeling/run_mlm.py

@@ -199,7 +199,7 @@ def main():
                 f"Output directory ({training_args.output_dir}) already exists and is not empty. "
                 "Use --overwrite_output_dir to overcome."
             )
-        elif last_checkpoint is not None:
+        elif last_checkpoint is not None and training_args.resume_from_checkpoint is None:
             logger.info(
                 f"Checkpoint detected, resuming training at {last_checkpoint}. To avoid this behavior, change "
                 "the `--output_dir` or add `--overwrite_output_dir` to train from scratch."
@@ -443,12 +443,11 @@ def main():
 
     # Training
     if training_args.do_train:
-        if last_checkpoint is not None:
+        checkpoint = None
+        if training_args.resume_from_checkpoint is not None:
+            checkpoint = training_args.resume_from_checkpoint
+        elif last_checkpoint is not None:
             checkpoint = last_checkpoint
-        elif model_args.model_name_or_path is not None and os.path.isdir(model_args.model_name_or_path):
-            checkpoint = model_args.model_name_or_path
-        else:
-            checkpoint = None
         train_result = trainer.train(resume_from_checkpoint=checkpoint)
         trainer.save_model()  # Saves the tokenizer too for easy upload
         metrics = train_result.metrics