How to train only the last convolutional layer?

Question

Could you help me with the code such that along with the dense layers also the last convolutional layer of Efficientnet is trained as well ?

features_url ="https://tfhub.dev/google/imagenet/efficientnet_v2_imagenet21k_b3/feature_vector/2"
img_shape = (299,299,3)
features_layer = hub.KerasLayer(features_url,
                                input_shape=img_shape)

# below commented code keeps all the cnn layers frozen, thus it does not work for me at the moment
#features_layer.trainable = False 

model = tf.keras.Sequential([
  features_layer,
  tf.keras.layers.Dense(256, activation = 'relu'),
  tf.keras.layers.Dense(64, activation = 'relu'),
  tf.keras.layers.Dense(4, activation = 'softmax')
]) 

In addition how can I save in a variable the name of the last convolutional layer ?