diff --git a/mindformers/core/callback/callback.py b/mindformers/core/callback/callback.py
index d14ec82880207d01123a6ce4f185468eed4526f4..17859e8f46c368ad0eb9391b2e2226267bb38680 100644
--- a/mindformers/core/callback/callback.py
+++ b/mindformers/core/callback/callback.py
@@ -43,6 +43,7 @@ from mindspore import (
     set_auto_parallel_context
 )
 from mindspore.train.callback import SummaryCollector
+from mindspore.train.callback._checkpoint import CheckpointManager
 from mindspore.nn.learning_rate_schedule import LearningRateSchedule
 from mindspore.train.serialization import _get_merged_param_data
 from mindspore.nn.cell import Cell
@@ -1178,6 +1179,14 @@ class CheckpointMonitor(ModelCheckpoint):
             self.last_ckpoint_file = None
             self.meta_updated = True
 
+        if self.save_network_params:
+            self._network_manager = CheckpointManager(config_ck.format)
+
+        if self.save_trainable_params:
+            self._trainable_manager = CheckpointManager(config_ck.format)
+
+        self.need_remove_extra_ckpt = False
+
     def print_savetime(self, record_step, batch_num):
         """print the time cost of saving checkpoint files."""
         epoch = int((record_step - 1) // batch_num + 1)
@@ -1243,6 +1252,7 @@ class CheckpointMonitor(ModelCheckpoint):
         # keep checkpoint files number equal max number.
         if self._config.keep_checkpoint_max and 0 < self._config.keep_checkpoint_max <= self._manager.ckpoint_num:
             self._manager.remove_oldest_ckpoint_file()
+            self.need_remove_extra_ckpt = True
         elif self._config.keep_checkpoint_per_n_minutes and self._config.keep_checkpoint_per_n_minutes > 0:
             # pylint: disable=E0203
             self._cur_time_for_keep = time.time()
@@ -1443,6 +1453,15 @@ class CheckpointMonitor(ModelCheckpoint):
                                    f"_{str(step_num_in_epoch)}.{self._config.format}")
             cb_cur_file = os.path.join(self.trainable_directory, cb_cur_ckpoint_file)
             os.makedirs(self.trainable_directory, exist_ok=True)
+
+            # update checkpoint file list.
+            self._trainable_manager.update_ckpoint_filelist(
+                self.trainable_directory, f"{self._prefix}-trainable_params"
+            )
+            # keep checkpoint files number equal max number.
+            if self.need_remove_extra_ckpt:
+                self._trainable_manager.remove_oldest_ckpoint_file()
+
             self.remove_redundancy(save_obj, cb_cur_file, {}, network)
             self.save_info_list[cb_params.cur_step_num]['trainable_params']['ckpt_file_path'] = cb_cur_file
             return
@@ -1453,9 +1472,18 @@ class CheckpointMonitor(ModelCheckpoint):
                                    f"_{str(step_num_in_epoch)}.{self._config.format}")
             cb_cur_file = os.path.join(self.network_directory, cb_cur_ckpoint_file)
             os.makedirs(self.network_directory, exist_ok=True)
+
+            # update checkpoint file list.
+            self._network_manager.update_ckpoint_filelist(self.network_directory, f"{self._prefix}-network")
+            # keep checkpoint files number equal max number.
+            if self.need_remove_extra_ckpt:
+                self._network_manager.remove_oldest_ckpoint_file()
+
             self.remove_redundancy(save_obj, cb_cur_file, {}, network)
             self.save_info_list[cb_params.cur_step_num]['network']['ckpt_file_path'] = cb_cur_file
 
+        self.need_remove_extra_ckpt = False
+
 
 
     def record_last_ckpt_to_json(self, epoch, step, ckpt_file):