save_model: checkpoint_done --> model_done

Author: gongel

paddlenlp/trainer/trainer.py

@@ -2051,10 +2051,10 @@ def save_model(self, output_dir: Optional[str] = None, merge_tensor_parallel: Op
             if not self.is_in_train:
                 self.args.unified_checkpoint_config = unified_checkpoint_config_backup
         if strtobool(os.getenv("FLAG_LLM_PDC", "False")):
-            # save checkpoint_done file to ensure checkpoint is complete
+            # save model_done file to ensure model is complete
             if self.args.should_save_model_state and self.args.should_save:
                 # For ckpt integrity
-                paddle.save(self.state.global_step, os.path.join(output_dir, ".checkpoint_done"))
+                paddle.save(self.state.global_step, os.path.join(output_dir, ".model_done"))
 
     def _save_checkpoint(self, model, metrics=None):
         # assert unwrap_model(model) is self.model, "internal model should be a reference to self.model"