Update README.md

README.md

@@ -16,7 +16,13 @@ This model was trained to detect fish in underwater **Grayscale Imagery** using
 - **Model Architecture**: YOLOv8n
 - **Task**: Object Detection (Fish Detection)
 - **Footage Type**: Grayscale(Black-and-White) Underwater Footage
-- **Classes**: Fish
+- **Classes**: 1 (fish)
+
+## Test Results
+![GIF description](./unsupervised_ai_test.gif)
+
+## Model Weights
+The model's weights can be found [here](./yolov8n_fish_trained.pt)
 
 # Intended Use
 - real time detections on Grayscale(Black-and-White) Underwater Footage
@@ -30,12 +36,6 @@ This model was trained to detect fish in underwater **Grayscale Imagery** using
 - Training Data: Quality and diversity of the grayscale underwater dataset, split into 80% training and 20% validation.
 - Training Parameters: Configured with 50 epochs, a 0.001 learning rate, and 416x416 image size for optimal model convergence.
 
-## Model Weights
-The model's weights can be found [here](./yolov8n_fish_trained.pt)
-
-## Test Results
-![GIF description](./unsupervised_ai_test.gif)
-
 ## Metrics
 Below are the key metrics from the model evaluation on the validation set: