Replies: 1 comment
-
|
Small models with a limited number of parameters generally do not require very strong data augmentation, and we have to replicate the data augmentation that officially attenuates training in comparison. |
Beta Was this translation helpful? Give feedback.
0 replies
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
-
Thanks for mmlab !
I notice that deit-tiny in mmpretrain is 74.5% while the performance in official deit is 72.2%.
I want to know the reason why the deit-tiny in mmpretrain performs better ?
Thanks a lot !
Beta Was this translation helpful? Give feedback.
All reactions