Update README.md

README.md

@@ -1,11 +1,13 @@
 ---
 license: mit
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+## Overview
 This repository contains the robust ImageNet models used in our paper ["Do adversarially robust imagenet models transfer better?"](https://arxiv.org/abs/2007.08489).
 
 See our papers's [GitHub repository](https://github.com/microsoft/robust-models-transfer) for more details!
 
-### Standard Accuracy of L2-Robust ImageNet Models 
+## Summary of our pretrained models
+#### Standard Accuracy of L2-Robust ImageNet Models 
 
 |Model|ε=0|ε=0.01|ε=0.03|ε=0.05|ε=0.1|ε=0.25|ε=0.5|ε=1.0|ε=3.0|ε=5.0|
 |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
@@ -24,7 +26,7 @@ ResNeXt50_32x4d|[77.38](https://huggingface.co/madrylab/robust-imagenet-models/r
 ShuffleNet|[64.25](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/shufflenet_l2_eps0.ckpt) | [43.32](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/shufflenet_l2_eps3.ckpt)
 VGG16_bn|[73.66](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/vgg16_bn_l2_eps0.ckpt) | [57.19](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/vgg16_bn_l2_eps3.ckpt)
 
-### Standard Accuracy of Linf-Robust ImageNet Models
+#### Standard Accuracy of Linf-Robust ImageNet Models
 |Model|ε=0.5/255|ε=1/255|ε=2/255|ε=4/255|ε=8/255|
 |---|:---:|:---:|:---:|:---:|:---:|
 |ResNet-18|[66.13](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/resnet18_linf_eps0.5.ckpt) | [63.46](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/resnet18_linf_eps1.0.ckpt) | [59.63](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/resnet18_linf_eps2.0.ckpt) | [52.49](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/resnet18_linf_eps4.0.ckpt) | [42.11](https://huggingface.co/madrylab/robust-imagenet-models/resolve/main/resnet18_linf_eps8.0.ckpt)