Update README.md

README.md

@@ -34,17 +34,20 @@ It achieves the following results on the evaluation set:
 - Accuracy: 0.9986
 
 ## Model description
-
-More information needed
+Multiclass image classification model based on [swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) and fine-tuned with Mango🥭 Leaf🍃🍂 Disease Dataset.
+Trained on 8 classes based on mango leaves health : 
+Anthracnose, Bacterial Canker, Cutting Weevil, Die Back, Gall Midge, Powdery Mildew, Sooty Mould, Healthy
 
 ## Intended uses & limitations
 
 More information needed
 
 ## Training and evaluation data
-Traning and evaluation data are from this Kaggle dataset (Mango🥭 Leaf🍃🍂 Disease Dataset)[https://www.kaggle.com/datasets/aryashah2k/mango-leaf-disease-dataset]
+Traning and evaluation data are from this Kaggle dataset [Mango🥭 Leaf🍃🍂 Disease Dataset](https://www.kaggle.com/datasets/aryashah2k/mango-leaf-disease-dataset).
+Amount of images used is 90% of total images (3600 of 4000, 450 images from each class).
 
 ## Training procedure
+Dataset split : 75% train set, 20% validation set, 5% test set.
 
 ### Training hyperparameters