check requirements.txt
pip install git+https://github.com/fra31/auto-attack
check ./script
MIMIR + more advanced fine-tuning (2-step APGD adversarial training, 300 epochs) for SOTA performance on ImageNet-1K
Model | Natural | AA | CheckPoint |
---|---|---|---|
ViT-S | 71.00 | 46.10 | Link |
ViT-B | 76.32 | 54.28 | Link |
Model | Natural | AA | CheckPoint |
---|---|---|---|
ViT-T | 84.82 | 52.96 | Link |
ViT-S | 88.11 | 53.18 | Link |
ViT-B | 89.30 | 54.55 | Link |
ConViT-T | 80.74 | 45.04 | Link |
ConViT-S | 87.49 | 52.54 | Link |
ConViT-B | 89.30 | 55.64 | Link |
Model | Natural | PGD 20 | CheckPoint |
---|---|---|---|
ViT-S | 74.60 | 54.56 | Link |
ViT-B | 75.88 | 55.42 | Link |
CaiT-XXS24 | 73.39 | 53.39 | Link |
CaiT-S36 | 76.05 | 56.78 | Link |
Model | Natural | PGD 20 | CheckPoint |
---|---|---|---|
ViT-S | 71.29 | 40.98 | Link |
ViT-B | 73.22 | 41.26 | Link |
CaiT-XXS24 | 69.90 | 40.53 | Link |
CaiT-S36 | 73.57 | 40.03 | Link |
Dataset | Model | CheckPoint |
---|---|---|
CIFAR-10 | ViT-T | Link |
CIFAR-10 | ViT-S | Link |
CIFAR-10 | ViT-B | Link |
CIFAR-10 | ConViT-T | Link |
CIFAR-10 | ConViT-S | Link |
CIFAR-10 | ConViT-B | Link |
ImageNet-1K | ViT-S | Link |
ImageNet-1K | ViT-B | Link |
ImageNet-1K | CaiT-XXS24 | Link |
ImageNet-1K | CaiT-S36 | Link |
This repository is built upon the following repositories:
https://github.com/facebookresearch/mae
https://github.com/wzekai99/DM-Improves-AT