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Good model results are very often mixed with random noise and getting good results is not constant even after many hours of training.
Maybe someone has found a solution to what needs to be changed in the model?
The text was updated successfully, but these errors were encountered:
The random initalization of the timesteps in sample_timesteps(self, n) is not ideal.We do not have control over the randomness of the timestep,hence some timesteps might not be sampled ,thus resulting to the model not being trained to predict noise on this time excluded steps.
Solution: Try look for a way to control the randomness of the sample times steps
Good model results are very often mixed with random noise and getting good results is not constant even after many hours of training.
Maybe someone has found a solution to what needs to be changed in the model?
The text was updated successfully, but these errors were encountered: