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

About transfer learning #49

Open
FeiMiBa opened this issue Sep 27, 2020 · 2 comments
Open

About transfer learning #49

FeiMiBa opened this issue Sep 27, 2020 · 2 comments

Comments

@FeiMiBa
Copy link

FeiMiBa commented Sep 27, 2020

Hi, I followed your instruction to train a model with MS1M training set, and I ended up achieving 99+@lfw, 95+@cfp, 95+@agedb. This pretrained model also achieved 97+ on my own testing set.

Then I used this pretrained model of mine to do transfer learning on my own training set, which is quite different from MS1M/LFW/CFP/AgeDB.... When I finished the tranfer learning, the final model achieved 99+ on my own testing set, but only 80+@lfw, 70+@cfp, 70+@agedb.

I wonder if I made any mistakes? Is there any ways to imporve the performance on my own testing set while remaining fair enough good performance on other testing sets?

Thank you for your time.

@cavalleria
Copy link
Owner

you can fix some layers params and finetune the remain layers, and do not overfitting in your own training set.

@FeiMiBa
Copy link
Author

FeiMiBa commented Sep 27, 2020

@cavalleria
That's exactly what I did with my model. I only trained on the last two layers, unfortunately that the results i got...

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