As far as I understand your problem, you’ve changed your model architecture because of the checkerboard artifacts, and your new model is not learning anything useful now.
Is this correct?
Do you have just this single image? If not, how many images are in your training, validation and test set?
Could you observe the losses for the separate datasets?
Is the training loss going down at all?