diff --git a/deepmd/pt/utils/dataset.py b/deepmd/pt/utils/dataset.py
index 267619b69d..e1deaaed8b 100644
--- a/deepmd/pt/utils/dataset.py
+++ b/deepmd/pt/utils/dataset.py
@@ -62,9 +62,14 @@ def get_frame_index_for_elements(self):
         element_counts = defaultdict(lambda: {"frames": 0, "indices": []})
         set_files = self._data_system.dirs
         base_offset = 0
+        global_type_name = {} 
         for set_file in set_files:
             element_data = self._data_system._load_type_mix(set_file)
             unique_elements = np.unique(element_data)
+            type_name = self._data_system.build_reidx_to_name_map(element_data,set_file)
+            for new_idx, elem_name in type_name.items():
+                if new_idx not in global_type_name:
+                    global_type_name[new_idx] = elem_name
             for elem in unique_elements:
                 frames_with_elem = np.any(element_data == elem, axis=1)
                 row_indices = np.where(frames_with_elem)[0]
@@ -73,7 +78,7 @@ def get_frame_index_for_elements(self):
                 element_counts[elem]["indices"].extend(row_indices_global.tolist())
             base_offset += element_data.shape[0]
         element_counts = dict(element_counts)
-        return element_counts
+        return element_counts, global_type_name
 
     def add_data_requirement(self, data_requirement: list[DataRequirementItem]) -> None:
         """Add data requirement for this data system."""
diff --git a/deepmd/pt/utils/stat.py b/deepmd/pt/utils/stat.py
index 36a77c198c..7c0a8aa265 100644
--- a/deepmd/pt/utils/stat.py
+++ b/deepmd/pt/utils/stat.py
@@ -60,6 +60,7 @@ def make_stat_input(
     log.info(f"Packing data for statistics from {len(datasets)} systems")
     total_element_types = set()
     global_element_counts = {}
+    global_type_name = {}
     collect_ele = defaultdict(int)
     if datasets[0].mixed_type:
         if enable_element_completion:
@@ -160,7 +161,10 @@ def finalize_stats(sys_stat):
 
         # get frame index
         if datasets[0].mixed_type and enable_element_completion:
-            element_counts = dataset.get_frame_index_for_elements()
+            element_counts, type_map = dataset.get_frame_index_for_elements()
+            for new_idx, elem_name in type_name.items():
+                if new_idx not in global_type_name:
+                    global_type_name[new_idx] = elem_name
             for elem, data in element_counts.items():
                 indices = data["indices"]
                 count = data["frames"]
@@ -195,10 +199,11 @@ def finalize_stats(sys_stat):
     if datasets[0].mixed_type and enable_element_completion:
         for elem, data in global_element_counts.items():
             indices_count = data["count"]
+            element_name = global_type_name.get(elem, f"<unknown-{elem}>")
             if indices_count < min_frames_per_element_forstat:
                 log.warning(
-                    f"The number of frames in your datasets with element {elem} is {indices_count}, "
-                    f"which is less than the required {min_frames_per_element_forstat}"
+                    f"The number of frames in your datasets with element {element_name} is {indices_count}, "
+                    f"which is less than the set {min_frames_per_element_forstat}"
                 )
         collect_elements = collect_ele.keys()
         missing_elements = total_element_types - collect_elements
diff --git a/deepmd/utils/data.py b/deepmd/utils/data.py
index fa01452bac..f5b9397df8 100644
--- a/deepmd/utils/data.py
+++ b/deepmd/utils/data.py
@@ -706,6 +706,20 @@ def _load_type_mix(self, set_name: DPPath):
             real_type = atom_type_mix_
         return real_type
 
+    def build_reidx_to_name_map(self,typemix, set_name: DPPath):
+        type_map = self.type_map
+        type_path = set_name / "real_atom_types.npy"
+        real_type = type_path.load_numpy().astype(np.int32).reshape([-1, self.natoms])
+        type_map_array = np.array(type_map, dtype=object)
+        reidx_to_name = {}
+        N, M = real_type.shape
+        for i in range(N):
+            for j in range(M):
+                old_val = int(real_type[i, j]) 
+                new_val = int(typemix[i, j])   
+                reidx_to_name[new_val] = type_map_array[old_val]
+        return reidx_to_name
+
     def _make_idx_map(self, atom_type):
         natoms = atom_type.shape[0]
         idx = np.arange(natoms, dtype=np.int64)