Update modified README

README.md

@@ -53,6 +53,11 @@ The dataset contains 13,955 imgaes of pills inside medication bottles, which are
 
 The dataset can be used to train image classification models, which might be helpful for identifying pills automatically to increase efficiency and reduce dispensing error of pills in pharmacy.
 
+### Example Use Case
+
+Here is a link to an [example use case](https://colab.research.google.com/drive/1UPaAnVacx3ZpOy_koWFwWIluhVZYOdhT?usp=sharing) of this dataset, which trained supervised models to predict the national drug code for each image. The highest accuracy obtained is about 97% using EfficientNetV2M as the pre-train model and Support Vector Machines as the supervised learning algorithm. 
+
+
 
 ## Dataset Structure
 
@@ -121,7 +126,3 @@ year={2022}
 
 This dataset contain all information from the source data. The only change made is to rearrange the structure by extracting the file names, which correspond to NDC and image id, and put them into separated columns.
 
-## Example Use Case
-
-Here is a link to an [example use case](https://colab.research.google.com/drive/1UPaAnVacx3ZpOy_koWFwWIluhVZYOdhT?usp=sharing) of this dataset, which trained supervised models to predict the national drug code for each image. The highest accuracy obtained is about 97% using EfficientNetV2M as the pre-train model and Support Vector Machines as the supervised learning algorithm. 
-