| fine-grained-image-classification-on-oxford-iiit-pets | ResNet-152-SAM | #10 | Accuracy: 93.3 |
| fine-grained-image-classification-on-oxford-iiit-pets | ViT-B/16- SAM | #11 | Accuracy: 93.1 |
| fine-grained-image-classification-on-oxford-iiit-pets | ViT-S/16- SAM | #12 | Accuracy: 92.9 |
| fine-grained-image-classification-on-oxford-iiit-pets | Mixer-B/16- SAM | #13 | Accuracy: 92.5 |
| fine-grained-image-classification-on-oxford-iiit-pets | ResNet-50-SAM | #14 | Accuracy: 91.6 |
| fine-grained-image-classification-on-oxford-iiit-pets | Mixer-S/16- SAM | #15 | Accuracy: 88.7 |
| domain-generalization-on-imagenet-r | ResNet-152x2-SAM | #36 | Top-1 Error Rate: 71.9 |
| domain-generalization-on-imagenet-r | ViT-B/16-SAM | #37 | Top-1 Error Rate: 73.6 |
| domain-generalization-on-imagenet-r | Mixer-B/8-SAM | #38 | Top-1 Error Rate: 76.5 |
| image-classification-on-imagenet-v2 | ResNet-152x2-SAM | #42 | Top 1 Accuracy: 69.6 |
| image-classification-on-imagenet-v2 | ViT-B/16-SAM | #49 | Top 1 Accuracy: 67.5 |
| image-classification-on-imagenet-v2 | Mixer-B/8-SAM | #52 | Top 1 Accuracy: 65.5 |
| image-classification-on-imagenet-real | ResNet-152x2-SAM | #43 | Accuracy: 86.4% |
| image-classification-on-imagenet-real | ViT-B/16-SAM | #49 | Accuracy: 85.2% |
| image-classification-on-imagenet-real | Mixer-B/8-SAM | #51 | Accuracy: 84.4% |
| domain-generalization-on-imagenet-c | ViT-B/16-SAM | #44 | Top 1 Accuracy: 56.5 |
| domain-generalization-on-imagenet-c | ResNet-152x2-SAM | #45 | Top 1 Accuracy: 55 |
| domain-generalization-on-imagenet-c | Mixer-B/8-SAM | #47 | Top 1 Accuracy: 48.9 |
| image-classification-on-cifar-10 | ViT-B/16- SAM | #47 | Percentage correct: 98.6 |
| image-classification-on-cifar-10 | ResNet-152-SAM | #66 | Percentage correct: 98.2 |
| image-classification-on-cifar-10 | ViT-S/16- SAM | #67 | Percentage correct: 98.2 |
| image-classification-on-cifar-10 | Mixer-B/16- SAM | #90 | Percentage correct: 97.8 |
| image-classification-on-cifar-10 | ResNet-50-SAM | #108 | Percentage correct: 97.4 |
| image-classification-on-cifar-10 | Mixer-S/16- SAM | #143 | Percentage correct: 96.1 |
| image-classification-on-flowers-102 | ViT-B/16- SAM | #54 | Accuracy: 91.8 |
| image-classification-on-flowers-102 | ViT-S/16- SAM | #55 | Accuracy: 91.5 |
| image-classification-on-flowers-102 | ResNet-152-SAM | #56 | Accuracy: 91.1 |
| image-classification-on-flowers-102 | ResNet-50-SAM | #57 | Accuracy: 90 |
| image-classification-on-flowers-102 | Mixer-B/16- SAM | #58 | Accuracy: 90 |
| image-classification-on-flowers-102 | Mixer-S/16- SAM | #60 | Accuracy: 87.9 |
| image-classification-on-cifar-100 | ViT-B/16- SAM | #55 | Percentage correct: 89.1 |
| image-classification-on-cifar-100 | ViT-S/16- SAM | #66 | Percentage correct: 87.6 |
| image-classification-on-cifar-100 | Mixer-B/16- SAM | #77 | Percentage correct: 86.4 |
| image-classification-on-cifar-100 | ResNet-50-SAM | #91 | Percentage correct: 85.2 |
| image-classification-on-cifar-100 | Mixer-S/16- SAM | #133 | Percentage correct: 82.4 |
| image-classification-on-imagenet | ResNet-152x2-SAM | #702 | Top 1 Accuracy: 81.1%Number of params: 236M |
| image-classification-on-imagenet | ViT-B/16-SAM | #768 | Top 1 Accuracy: 79.9%Number of params: 87M |
| image-classification-on-imagenet | Mixer-B/8-SAM | #831 | Top 1 Accuracy: 79%Number of params: 64M |