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

Question about the w(t) ramp-up length when using Mean-teacher model #1

Open
sanyouwu opened this issue Aug 16, 2019 · 3 comments
Open

Comments

@sanyouwu
Copy link

Hi, thanks for your contributions!
Meanwhile, I am curious about the warm ramp-up function w(t) when you use Mean-Teacher model+ your SNTG. Did you set the ramp-up length is 80 epochs (in your paper Appendix A) or 5 in (Mean-Teacher code).

@sanyouwu
Copy link
Author

@xinmei9322

@xinmei9322
Copy link
Owner

@sanyouwu Sorry for the late reply. I just saw the message. I set the ramp-up length to 5, the same as that in the original Mean-Teacher code. Actually, the implementation is based on their public code and the hyper-parameters remain the same except the new hyper-parameter we introduced.

@sanyouwu
Copy link
Author

Alright, thanks. But I think it is more reasonable for increase the value of w(t) instead of 5. You know, the accuracy of the classification is low at the start of training. I meaning, why not you use two ramp-up function w1(t) and w2(t), and w1(t) (5 epochs)is for consistency loss while w2(t) used for contrastive loss(larger than 5 epochs). @xinmei9322

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

2 participants