Skip to content
This repository has been archived by the owner on Mar 15, 2024. It is now read-only.

Config file of ViT-B/16 #195

Open
shashankvkt opened this issue Oct 21, 2022 · 2 comments
Open

Config file of ViT-B/16 #195

shashankvkt opened this issue Oct 21, 2022 · 2 comments

Comments

@shashankvkt
Copy link

Hi Hugo,
Thanks for this sharing your amazing work. I was trying to train ViT-B/16 from scratch on ImageNet-1k using the hyperparams reported in your DeIT paper. I'm pretty sure I'm missing something, but I'm unable to reach 81.8%. With the hyperparams I use, I get around 78.6% which is even worse than ViT-S/16.

Could you please share the training command line for ViT-B/16 or share the config file for the same?
Thanks a lot.

@TouvronHugo
Copy link
Contributor

TouvronHugo commented Oct 30, 2022

Hi @shashankvkt,
Thanks for your message. The command line is:
python run_with_submitit.py --model deit_base_patch16_224 --data-path /path/to/imagenet
Best,
Hugo

(It's here in the README.)

@shashankvkt
Copy link
Author

Hi Hugo,
Thanks for your response. I had used exactly the same command line, but this time I get 79.2% (0.6% increase than previous) and still dont get close to 81.8. I use a smaller batch size of 1024 on 4 GPUs, with a learning rate 1e-3, warm up of 5 epochs. Do you think it's due to the batch size that is causing this poor performance?
Thanks

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

No branches or pull requests

2 participants