Update README.md

README.md

@@ -1,3 +1,46 @@
 ---
 license: mit
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+## CACR checkpoint repository
+
+### For implementation details, please refer to our [Github Repo](https://github.com/JegZheng/CACR-SSL)
+
+
+#### ImageNet pretrained, performance of linear classification on ImageNet
+<table><tbody>
+<!-- START TABLE -->
+<!-- TABLE HEADER -->
+<th valign="left">model</th>
+<th valign="left">pretrain<br/>epochs</th>
+<th valign="left">linear<br/>acc</th>
+<!-- TABLE BODY -->
+<tr>
+<td align="left">ResNet50</td>
+<td align="left">1000</td>
+<td align="left">74.7</td>
+</tr>
+<tr>
+<td align="left">ViT-Base</td>
+<td align="left">300</td>
+<td align="left">77.1</td>
+</tr>
+</tbody></table>
+
+#### ImageNet pretrained, performance of linear classification on 20 Image in the Wild datasets
+Please feel free to check our learned representation performance in [Image in the Wild Challenge](https://eval.ai/web/challenges/challenge-page/1832/leaderboard/4301).
+
+
+### Citation
+Please cite our work if you find it is helpful. Thank you!
+```
+@article{
+  zheng2023contrastive,
+  title={Contrastive Attraction and Contrastive Repulsion for Representation Learning},
+  author={Huangjie Zheng and Xu Chen and Jiangchao Yao and Hongxia Yang and Chunyuan Li and Ya Zhang and Hao Zhang and Ivor Tsang and Jingren Zhou and Mingyuan Zhou},
+  journal={Transactions on Machine Learning Research},
+  issn={2835-8856},
+  year={2023},
+  url={https://openreview.net/forum?id=f39UIDkwwc},
+}
+```
+