sampling issue about diffuseq HOT 3 OPEN

Actually it's not easy, because training and inference stages are not strictly symmetrical. You can try to recover 50% noised data instead of pure Gaussian noise.

from diffuseq.

Hi,
I think the model is not well-trained so it can not recover meaningful tokens. Maybe you could try other hyper-params. Another concern is that the size of your dataset is a little bit small.

from diffuseq.

Thank you for the thoughts/suggestions. In this kind of model, is there any metric that I could access during the training to check if the model is well-trained? I ask that because the training and validation loss performed well in this case, but even so, the model seems not to be well-trained.

from diffuseq.