Training of Yolo

# Optimization Functions               
optimizer = Adam(lr=0.5e-4, beta_1=0.9, beta_2=0.999, epsilon=1e-08, decay=0.0)
#optimizer = SGD(lr=1e-4, decay=0.0005, momentum=0.9)
#optimizer = RMSprop(lr=1e-4, rho=0.9, epsilon=1e-08, decay=0.0)

model.compile(loss=custom_loss, optimizer=optimizer)

model.fit_generator(generator        = train_batch, 
                    steps_per_epoch  = int(len(train_batch)/16), 
                    epochs           = 100, 
                    verbose          = 1,
                    validation_data  = valid_batch,
                    validation_steps = int(len(valid_batch)/16),
                    callbacks        = [early_stop, checkpoint,learning_rate_reduction],#, tensorboard], 
                    max_queue_size   = 3)