diff --git a/modelscope/utils/tensor_utils.py b/modelscope/utils/tensor_utils.py
index 3e6075f0..01b68f78 100644
--- a/modelscope/utils/tensor_utils.py
+++ b/modelscope/utils/tensor_utils.py
@@ -41,12 +41,16 @@ def torch_default_data_collator(features):
                 first['label'], torch.Tensor) else first['label']
             # the msdataset return a 0-dimension np.array with a single value, the following part handle this.
             if isinstance(label, np.ndarray):
+                src_dtype = label[()].dtype
                 dtype = torch.long if label[(
                 )].dtype == np.int64 else torch.float
             else:
+                src_dtype = type(label)
                 dtype = torch.long if isinstance(label, int) else torch.float
+            # add dtype to np.array to fix "TypeError: can't convert np.ndarray of type numpy.object_"
             batch['labels'] = torch.tensor(
-                np.array([f['label'] for f in features]), dtype=dtype)
+                np.array([f['label'] for f in features], dtype=src_dtype),
+                dtype=dtype)
         elif 'label_ids' in first and first['label_ids'] is not None:
             if isinstance(first['label_ids'], torch.Tensor):
                 batch['labels'] = torch.stack(