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This repository has been archived by the owner on Mar 15, 2024. It is now read-only.
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.
The text was updated successfully, but these errors were encountered:
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
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
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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.
The text was updated successfully, but these errors were encountered: