text: Title: feature request about resuming model training with epochs change
  Body: ### Scene
  
  given trained model total 100 epochs done, then I want to resume training based on previous trained model and increasing/decreasing some epochs.
  
  first 100 epochs:
  ```python
  model = YOLO("yolo.pt")
  results = model.train(
      data="datasets/xxx.yaml",
      save_period=2,
      epochs=100,
  )
  ```
  
  then, resume training and change epochs:
  ```python
  model = YOLO("epoch90.pt")
  results = model.train(
      data="datasets/xxx.yaml",
      save_period=2,
      epochs=300,  # more epochs
      resume=True, # resume flag
  )
  ```
  
  but `epochs=300` not works, it still stops at 100.
  
  As already pointed in https://github.com/ultralytics/ultralytics/issues/16402 and https://github.com/ultralytics/ultralytics/issues/18154 . I'm wondering why changing epochs when resuming is not supported in current code base?
  
  Is it possible to support it?
  
  