Update README.md

README.md

@@ -16,6 +16,7 @@ This model is a garbage classification system built on the ResNet50 architecture
 
 ## Model Architecture
 Base Model: ResNet50 (pre-trained on ImageNet).
+
 Modifications: The final fully connected layer was modified to output 12 classes instead of the default 1000 classes used in ImageNet.
 
 ## Intended Use
@@ -116,7 +117,6 @@ Epoch 9 completed in 2181.82 seconds.
 Epoch 10/10
 ----------
 train Loss: 0.2604 Acc: 0.9136
-
 valid Loss: 0.2076 Acc: 0.9326
 
 Training complete in 362m 11s
@@ -133,6 +133,6 @@ This ResNet50-based garbage classification model shows promising performance for
 Further details and the code for this model can be found in the experiment tracking system. 
 
 ## Potential Improvements
-- Real-world data collection to reduce bias.
-- Data augmentation to handle edge cases like occluded or partially damaged garbage items.
+- Real-world data collection (preferably of items in poor or trash-like conditions) to reduce bias.
+- More data augmentation to handle edge cases like occluded or partially damaged garbage items.
 - Deploying the model in edge devices for real-time classification at waste management facilities.