diff --git a/paddlenlp/trainer/auto_trainer.py b/paddlenlp/trainer/auto_trainer.py
index 6fc086b54584..81dec37b611e 100644
--- a/paddlenlp/trainer/auto_trainer.py
+++ b/paddlenlp/trainer/auto_trainer.py
@@ -687,7 +687,13 @@ def _save_checkpoint(self, model, metrics=None):
                 # For ckpt integrity
                 paddle.save(self.state.global_step, os.path.join(output_dir, ".checkpoint_done"))
 
-    def _save(self, output_dir: Optional[str] = None, state_dict=None, merge_tensor_parallel=False):
+    def _save(
+        self,
+        output_dir: Optional[str] = None,
+        state_dict=None,
+        merge_tensor_parallel=False,
+        signal_dir: Optional[str] = None,
+    ):
         output_dir = output_dir if output_dir is not None else self.args.output_dir
         os.makedirs(output_dir, exist_ok=True)
         logger.info(f"Saving model checkpoint to {output_dir}")
diff --git a/paddlenlp/trainer/trainer.py b/paddlenlp/trainer/trainer.py
index 7c7ad82ccc11..ddc872ad6173 100644
--- a/paddlenlp/trainer/trainer.py
+++ b/paddlenlp/trainer/trainer.py
@@ -581,7 +581,9 @@ def _load_from_checkpoint(self, resume_from_checkpoint=None):
         # Load potential model checkpoint
         if isinstance(resume_from_checkpoint, bool) and resume_from_checkpoint:
             uc_async_save = self.args.unified_checkpoint and "async_save" in self.args.unified_checkpoint_config
-            resume_from_checkpoint = get_last_checkpoint(self.args.output_dir, uc_async_save)
+            resume_from_checkpoint = get_last_checkpoint(
+                self.args.output_dir, signal_folder=self.args.output_signal_dir, uc_async_save=uc_async_save
+            )
             if resume_from_checkpoint is None:
                 raise ValueError(f"No valid checkpoint found in output directory ({self.args.output_dir})")
 
@@ -2509,7 +2511,7 @@ def _save_checkpoint(self, model, metrics=None):
         need_to_rotate_checkpoints = need_to_rotate_checkpoints and self.args.local_rank == 0
         if need_to_rotate_checkpoints:
             self._rotate_checkpoints(use_mtime=True, output_dir=run_dir)
-            self._rotate_checkpoints(use_mtime=False, output_dir=run_signal_dir)
+            self._rotate_checkpoints(use_mtime=True, output_dir=run_signal_dir)
 
         if strtobool(os.getenv("FLAG_LLM_PDC", "False")) and not ("async_save" in self.args.unified_checkpoint_config):
             # save checkpoint_done file to ensure checkpoint is complete