Update README.md

README.md

@@ -3,7 +3,7 @@ license: apache-2.0
 task_categories:
 - image-classification
 size_categories:
-- n<1K
+- 100K<n<1M
 ---
 ## Neglected Free Lunch – Learning Image Classifiers Using Annotation Byproducts | [Paper](https://arxiv.org/abs/2303.17595)
 
@@ -23,7 +23,7 @@ Supervised learning of image classifiers distills human knowledge into a paramet
 
 Our insight is that such **annotation byproducts** *Z* provide approximate human attention that weakly guides the model to focus on the foreground cues, reducing spurious correlations and discouraging shortcut learning. 
 
-We have created **ImageNet-AB** and **COCO-AB** to verify this:
+We have created **ImageNet-AB** and **COCO-AB** to verify this.
 
 They are ImageNet and COCO training sets enriched with sample-wise annotation byproducts, collected by replicating the respective original annotation tasks. 
 
@@ -83,5 +83,4 @@ SOFTWARE.
   journal={arXiv preprint arXiv:2303.17595},
   year = {2023}
 }
-```
-
+```