Getting the weight for only the base model

Question

I have this model:

def get_resnet_simclr(hidden_1, hidden_2, hidden_3):
    
    base_model = tf.keras.applications.ResNet50(include_top=False, weights=None, input_shape=(224, 224, 3))
    base_model.trainable = True
    
    inputs = Input((224, 224, 3))
    h = base_model(inputs, training=True)
    h = GlobalAveragePooling2D()(h )

    projection_1 = Dense(hidden_1)(h)
    projection_1 = Activation("relu")(projection_1)
    projection_2 = Dense(hidden_2)(projection_1)
    projection_2 = Activation("relu")(projection_2)
    projection_3 = Dense(hidden_3)(projection_2)

    resnet_simclr = Model(inputs, projection_3)

    return resnet_simclr 

after training this model. I need only to save the weight for the base_model (ResNet50), without the GlobalAveragePooling2D, Dense, Activation ... etc. How do I do that.