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> No it hasn't https://paperswithcode.com/sota/image-classification-on-imag https://paperswithcode.com/sota/image-classification-on-imag... We were talking abo

by trott 6y ago

> No it hasn't https://paperswithcode.com/sota/image-classification-on-imag https://paperswithcode.com/sota/image-classification-on-imag... We were talking about models trained on ImageNet, specifically about the trade-off between accuracy and FLOPs. But the higher-accuracy models listed in your link use extra data. So it's not quite the same benchmark we were talking about.

The_rationalist 6y ago
The deepmind paper NFNet-F4+ you were talking about also has external training data. The number one in accuracy (Meta pseudo labels) is also faster for inference (390M vs 570M parameters) vs the deepmind one. So what are you disagreeing with?
- trott 6y ago
  > The deepmind paper NFNet-F4+ you were talking about also has external training data. @dheera and I did not mention NFNet-F4+. All models, tables, figures and numbers that we did mention resulted from training on ImageNet alone.