Update README.md

README.md

@@ -40,7 +40,7 @@ The goal of the competition was to apply novel approaches to achieve the highest
 We were given a labeled dataset of 3,926 images and an unlabeled dataset of 4,000 test images.
 Out of 32 groups and 1,083 submissions, we achieved the #1 accuracy on the test set with a score of 0.87950.
 
-## Training Details
+### Training Details
 The model we are finetuning, microsoft/swin-large-patch4-window12-384-in22k, was pre-trained on imagenet-21k, see https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k.
 
 #### Preprocessing
@@ -71,10 +71,15 @@ We finetuned the model on 3533 samples of the labeled dataset we were given, str
 
 *parameters were intentionally left out because of poor results
 
-## Evaluation Data
+### Evaluation Data
 The evaluation data is a subset of the cub-200-2011 dataset, https://paperswithcode.com/dataset/cub-200-2011
 We evaluated the model on 393 samples of the labeled dataset we were given, stratified on the label.
 
 #### Testing Data
 
 The testing data is a subset of an unlabeled subset of the cub-200-2011 dataset, https://paperswithcode.com/dataset/cub-200-2011 of 4000 images. 
+
+### Poster
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/624d888b0ce29222ad64c3d6/XbH4M6aL8iE4Hy75xfaHc.png)
+