diff --git a/recommenders/models/newsrec/models/base_model.py b/recommenders/models/newsrec/models/base_model.py
index e0f4da017..344ea8f7c 100644
--- a/recommenders/models/newsrec/models/base_model.py
+++ b/recommenders/models/newsrec/models/base_model.py
@@ -186,6 +186,8 @@ def fit(
         valid_behaviors_file,
         test_news_file=None,
         test_behaviors_file=None,
+        step_limit=None,
+
     ):
         """Fit the model with train_file. Evaluate the model on valid_file per epoch to observe the training status.
         If test_news_file is not None, evaluate it too.
@@ -212,6 +214,8 @@ def fit(
             )
 
             for batch_data_input in tqdm_util:
+                if step_limit is not None and step>=step_limit:
+                    break
 
                 step_result = self.train(batch_data_input)
                 step_data_loss = step_result
diff --git a/tests/smoke/recommenders/recommender/test_newsrec_model.py b/tests/smoke/recommenders/recommender/test_newsrec_model.py
index 7cad05ba3..db609f098 100644
--- a/tests/smoke/recommenders/recommender/test_newsrec_model.py
+++ b/tests/smoke/recommenders/recommender/test_newsrec_model.py
@@ -62,7 +62,7 @@ def test_model_nrms(mind_resource_path):
     assert model.run_eval(valid_news_file, valid_behaviors_file) is not None
     assert isinstance(
         model.fit(
-            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file
+            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file,step_limit=10
         ),
         BaseModel,
     )
@@ -115,7 +115,7 @@ def test_model_naml(mind_resource_path):
     assert model.run_eval(valid_news_file, valid_behaviors_file) is not None
     assert isinstance(
         model.fit(
-            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file
+            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file,step_limit=10
         ),
         BaseModel,
     )
@@ -166,7 +166,7 @@ def test_model_lstur(mind_resource_path):
     assert model.run_eval(valid_news_file, valid_behaviors_file) is not None
     assert isinstance(
         model.fit(
-            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file
+            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file,step_limit=10
         ),
         BaseModel,
     )
@@ -217,7 +217,7 @@ def test_model_npa(mind_resource_path):
     assert model.run_eval(valid_news_file, valid_behaviors_file) is not None
     assert isinstance(
         model.fit(
-            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file
+            train_news_file, train_behaviors_file, valid_news_file, valid_behaviors_file,step_limit=10
         ),
         BaseModel,
     )