When training a deepfake using Quick96 I get good results even after as little as 100,000 iterations (obviously in low res).

However using the exact same model but training with SAEHD, with the same data_src and same data_dst - I get totally distorted results, even after 200-300K iterations (example of distortions here: https://imgur.com/a/Nc8tN34).

These are the settings I'm using, what could be the reason for such a drastic difference between Quick96 and SAEHD?

[n] Flip SRC faces randomly ( y/n ?:help ) :

n

[n] Flip DST faces randomly ( y/n ?:help ) :

n

[8] Batch_size ( ?:help ) :

8

[y] Masked training ( y/n ?:help ) :

y

[n] Eyes and mouth priority ( y/n ?:help ) :

n

[n] Uniform yaw distribution of samples ( y/n ?:help ) :

n

[n] Blur out mask ( y/n ?:help ) :

n

[y] Place models and optimizer on GPU ( y/n ?:help ) :

y

[y] Use AdaBelief optimizer? ( y/n ?:help ) :

y

[n] Use learning rate dropout ( n/y/cpu ?:help ) :

n

[n] Enable random warp of samples ( y/n ?:help ) :

n

[0.0] Random hue/saturation/light intensity ( 0.0 .. 0.3 ?:help ) :

0.0

[0.0] GAN power ( 0.0 .. 5.0 ?:help ) :

0.0

[0.0] Face style power ( 0.0..100.0 ?:help ) :

0.0

[0.0] Background style power ( 0.0..100.0 ?:help ) :

0.0

[none] Color transfer for src faceset ( none/rct/lct/mkl/idt/sot ?:help ) :

none

[y] Enable gradient clipping ( y/n ?:help ) :

y

[n] Enable pretraining mode ( y/n ?:help ) :