text: Title: Why the mAP increase only 0.001 percent every epoch. Any suggestion how to make fast?
  Body: ### Search before asking
  
  - [x] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and found no similar questions.
  
  
  ### Question
  
  Hello,
  
  I’ve been training a YOLO model on a custom dataset and have noticed that the mean Average Precision (mAP) increases by approximately 0.001% with each epoch. The training process doesn't provide clear guidance on when to stop, and I'm concerned that the model might be overfitting. However, the confusion matrix at epoch 400 doesn't seem to indicate overfitting.
  
  Do you have any suggestions on how to determine the optimal stopping point or strategies to prevent potential overfitting?
  
  Thank you!
   
  
  <img width="855" alt="Image" src="https://github.com/user-attachments/assets/3cd039bc-5ed8-4ea2-b646-1b47bfd0c1f5" />
  
  
  Thanks
  
  ### Additional
  
  _No response_