Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

The model could not be fitted if not predict xstart #89

Open
JJLi0427 opened this issue May 11, 2024 · 4 comments
Open

The model could not be fitted if not predict xstart #89

JJLi0427 opened this issue May 11, 2024 · 4 comments

Comments

@JJLi0427
Copy link

Thank you so much for sharing this great work.
I try to use DiT to my dataset, but I meet some problem when I train model using predict_xstart = False. The loss down a little and seem to stuck at a hight level and won't be down, when I use predict_xstart = True the loss down quickly.

@santisy
Copy link

santisy commented May 14, 2024

So can you confirm that when using predict_xtart=True, the result would be much better?

@JJLi0427
Copy link
Author

So can you confirm that when using predict_xtart=True, the result would be much better?

According to my dataset experiment predict_xtart=True can converge quickly

@XijiaWang
Copy link

According to my dataset experiment predict_xtart=True can converge quickly

@JJLi0427
Hello, I encountered the same problem, have you found the reason?

@JJLi0427
Copy link
Author

According to my dataset experiment predict_xtart=True can converge quickly

@JJLi0427 Hello, I encountered the same problem, have you found the reason?

This seems to be because there is a problem with the implementation of the denoising function, and I only used predict xstart to do my task later.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants