| domain-generalization-on-imagenet-a | GFNet-S | #30 | Top-1 accuracy %: 14.3 |
| domain-generalization-on-imagenet-c | GFNet-S | #30 | mean Corruption Error (mCE): 53.8 |
| image-classification-on-cifar-10 | GFNet-H-B | #25 | Percentage correct: 99.0 |
| image-classification-on-cifar-100 | GFNet-H-B | #23 | Percentage correct: 90.3PARAMS: 54M |
| image-classification-on-flowers-102 | GFNet-H-B | #19 | Accuracy: 98.8PARAMS: 54M |
| image-classification-on-imagenet | GFNet-H-B | #471 | Top 1 Accuracy: 82.9%Number of params: 54MGFLOPs: 8.6 |
| image-classification-on-stanford-cars | GFNet-H-B | #9 | Accuracy: 93.2 |