diff --git a/src/twomartens/masterthesis/ssd.py b/src/twomartens/masterthesis/ssd.py
index 14354d9..feedd9f 100644
--- a/src/twomartens/masterthesis/ssd.py
+++ b/src/twomartens/masterthesis/ssd.py
@@ -80,6 +80,18 @@ class SSD:
         # load existing weights
         if weights_path is not None:
             self._model.load_weights(weights_path, by_name=True)
+        
+        if mode == "training":
+            # set non-classifier layers to non-trainable
+            classifier_names = ['conv4_3_norm_mbox_conf',
+                                'fc7_mbox_conf',
+                                'conv6_2_mbox_conf',
+                                'conv7_2_mbox_conf',
+                                'conv8_2_mbox_conf',
+                                'conv9_2_mbox_conf']
+            for layer in self._model.layers:
+                if layer.name not in classifier_names:
+                    layer.trainable = False
     
     def __call__(self, inputs: tf.Tensor, *args, **kwargs) -> tf.Tensor:
         return self._model(inputs)
@@ -104,6 +116,18 @@ class DropoutSSD:
         # load existing weights
         if weights_path is not None:
             self._model.load_weights(weights_path, by_name=True)
+
+        if mode == "training":
+            # set non-classifier layers to non-trainable
+            classifier_names = ['conv4_3_norm_mbox_conf',
+                                'fc7_mbox_conf',
+                                'conv6_2_mbox_conf',
+                                'conv7_2_mbox_conf',
+                                'conv8_2_mbox_conf',
+                                'conv9_2_mbox_conf']
+            for layer in self._model.layers:
+                if layer.name not in classifier_names:
+                    layer.trainable = False
     
     def __call__(self, inputs: tf.Tensor, *args, **kwargs) -> tf.Tensor:
         return self._model(inputs)