The loss/localization loss graph demonstrates a consistent downward trend, showcasing the model's substantial improvement over training epochs

The rapid initial decline followed by a gradual convergence to a minimal value, indicating the model's effective learning and fine-tuning in object detection.

This progressive decrease signifies successful reduction in both classification and localization errors.

Overall, the graph reflects the model's impressive performance enhancement, ensuring robust object detection capabilities with minimized localization discrepancies.

The loss classification shows a steady decrease, indicating improved accuracy in object classification.

The loss/total exhibits a consistent downward trend, signifying effective overall optimization and enhanced model performance in object detection tasks