Update README.md

README.md

@@ -1,13 +1,15 @@
 ---
 library_name: transformers
 tags: []
+base_model: microsoft/conditional-detr-resnet-50
 ---
 
-# Model Card for Model ID
+# Model Overview
 
-This model is a DETR-based object detection model trained for medical image analysis, specifically focused on detecting different classes of pneumonia in chest X-rays. The model can identify four categories: Pneumonia, Normal, Pneumonia_bacteria, and Pneumonia_virus. It is well-suited for diagnostic support tasks where automated detection of pneumonia and its types is needed.
+This model is a DETR-based object detection model trained for medical image analysis,
+4 classes : 0:Pneumonia, 1:Normal, 2:Pneumonia_bacteria, and 3:Pneumonia_virus
 
-# Model Description
+## Model Description
 Model Architecture: DEtection TRansformers (DETR)
 Training Data: Trained on a custom dataset of annotated medical images
 Intended Use: Designed for analyzing chest X-ray images to detect the presence and type of pneumonia, or classify as normal..