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

Training option #3

Open
pokaxpoka opened this issue Aug 19, 2018 · 1 comment
Open

Training option #3

pokaxpoka opened this issue Aug 19, 2018 · 1 comment

Comments

@pokaxpoka
Copy link

Hi, thank you for sharing the code. Is it possible to clarify the all training options (e.g., python train_model.py -d mnist -m d2l -e 50 -b 128 -r 40 ) for the results on the paper? It'll be very useful in reproducing your results.

Thanks

@xingjunm
Copy link
Owner

xingjunm commented Nov 7, 2018

For CIFAR-10:

  1. clean: train_model.py '-d', 'cifar-10', '-m', 'd2l', '-e', '120', '-b', '128', '-r', '0'
  2. 20%: train_model.py '-d', 'cifar-10', '-m', 'd2l', '-e', '120', '-b', '128', '-r', '20'
  3. 40%: train_model.py '-d', 'cifar-10', '-m', 'd2l', '-e', '120', '-b', '128', '-r', '40'
  4. 60%: train_model.py '-d', 'cifar-10', '-m', 'd2l', '-e', '120', '-b', '128', '-r', '60'

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