diff --git a/tests/test_commons.py b/tests/test_commons.py
new file mode 100644
index 000000000..5e8be38a3
--- /dev/null
+++ b/tests/test_commons.py
@@ -0,0 +1,46 @@
+# built-in dependencies
+import os
+import pytest
+
+# project dependencies
+from deepface.commons import folder_utils, weight_utils, package_utils
+from deepface.commons.logger import Logger
+
+logger = Logger()
+
+tf_version = package_utils.get_tf_major_version()
+
+if tf_version == 1:
+    from keras.models import Sequential
+    from keras.layers import (
+        Dropout,
+        Dense,
+    )
+else:
+    from tensorflow.keras.models import Sequential
+    from tensorflow.keras.layers import (
+        Dropout,
+        Dense,
+    )
+
+
+def test_loading_broken_weights():
+    home = folder_utils.get_deepface_home()
+    weight_file = os.path.join(home, ".deepface/weights/vgg_face_weights.h5")
+
+    # construct a dummy model
+    model = Sequential()
+
+    # Add layers to the model
+    model.add(
+        Dense(units=64, activation="relu", input_shape=(100,))
+    )  # Input layer with 100 features
+    model.add(Dropout(0.5))  # Dropout layer to prevent overfitting
+    model.add(Dense(units=32, activation="relu"))  # Hidden layer
+    model.add(Dense(units=10, activation="softmax"))  # Output layer with 10 classes
+
+    # vgg's weights cannot be loaded to this model
+    with pytest.raises(ValueError, match="Exception while loading pre-trained weights from"):
+        model = weight_utils.load_model_weights(model=model, weight_file=weight_file)
+
+    logger.info("✅ test loading broken weight file is done")
diff --git a/tests/test_verify.py b/tests/test_verify.py
index 979b1bd40..2a6951b71 100644
--- a/tests/test_verify.py
+++ b/tests/test_verify.py
@@ -1,13 +1,9 @@
-# built-in dependencies
-import os
-
 # 3rd party dependencies
 import pytest
 import cv2
 
 # project dependencies
 from deepface import DeepFace
-from deepface.commons import folder_utils, package_utils
 from deepface.commons.logger import Logger
 
 logger = Logger()
@@ -192,35 +188,3 @@ def test_verify_for_nested_embeddings():
         _ = DeepFace.verify(img1_path=img1_embeddings, img2_path=img2_path)
 
     logger.info("✅ test verify for nested embeddings is done")
-
-
-def test_verify_for_broken_weights():
-    home = folder_utils.get_deepface_home()
-
-    # we are not performing anything with model deepid
-
-    weights_file = os.path.join(home, ".deepface/weights/deepid_keras_weights.h5")
-    backup_file = os.path.join(home, ".deepface/weights/deepid_keras_weights_backup.h5")
-
-    restore = False
-    # backup original weight file
-    if os.path.exists(weights_file) is True:
-        os.rename(weights_file, backup_file)
-        restore = True
-
-    # Create a dummy vgg_face_weights.h5 file
-    with open(weights_file, "w", encoding="UTF-8") as f:
-        f.write("dummy content")
-
-    with pytest.raises(ValueError, match="Exception while loading pre-trained weights from"):
-        _ = DeepFace.verify(
-            img1_path="dataset/img1.jpg",
-            img2_path="dataset/img2.jpg",
-            model_name="DeepId",
-        )
-
-    if restore:
-        os.remove(weights_file)
-        os.rename(backup_file, weights_file)
-
-    logger.info("✅ test verify for broken weight file is done")