Hello,
In the lab “Art Generation with Neural Style Transfer,” the hyperparameters alpha and beta are used to weight the importance of the content and style costs, respectively. The initially specified values for these hyperparameters were alpha = 10 and beta = 40. When I tried swapping the values, the resulting images did not differ significantly in terms of representing the style and content images. What could be the reason?
Training hyperparameters for training session 1:
STYLE_LAYERS = [
(‘block1_conv1’, 0.2),
(‘block2_conv1’, 0.2),
(‘block3_conv1’, 0.2),
(‘block4_conv1’, 0.2),
(‘block5_conv1’, 0.2)]
alpha = 10, beta = 40
epochs = 20000
optimizer = tf.keras.optimizers.Adam(learning_rate=0.001)
Resulting image:
Training hyperparameters for training session 2:
STYLE_LAYERS = [
(‘block1_conv1’, 0.2),
(‘block2_conv1’, 0.2),
(‘block3_conv1’, 0.2),
(‘block4_conv1’, 0.2),
(‘block5_conv1’, 0.2)]
alpha = 40, beta = 10
epochs = 20000
optimizer = tf.keras.optimizers.Adam(learning_rate=0.001)
Resulting Image:
Thanks in advance!