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

adaptation question, discriminator acc=0.5 representing best adaptation? #9

Open
dupanfei1 opened this issue May 9, 2018 · 2 comments

Comments

@dupanfei1
Copy link

Thanks for the code.
I changed the dataset. But the adaptation process didn't converge( acc=0.5 represents convergence?), and just get 14% domain adaptation accrucy.

Epoch [457/600] Step [100/200]:d_loss=0.32023 g_loss=3.27941 acc=0.89000

what parameters I need to change?
Should I normalize the source and target dataset?
Thank you!

@Nyn-ynu
Copy link

Nyn-ynu commented Jun 6, 2020

I meet the same question as yours. No matter what i do, the acc just fluctuates between 10% and 15%. Domain discriminator and classifier's game out of control in total

@hfutyanhuan
Copy link

@dupanfei1 请问你最终解决了这个问题了吗

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