Hi Frank,
Thank you for your replies and suggestions. Regarding the following part:

There’s nothing wrong nor inconsistent about doing things this way
(although it does seem like you would be standing on your head), but
the meaning of your model’s predictions is no longer the same as
if you had trained it as a conventional single-label, four-class model.
Instead, your model is making multi-label, two-class predictions, albeit
encoded in an unusual way.

Isn’t it true when I consider both ‘components’, I should push the model to train for predicting ‘both components’, in other words, a four-class model – this way through ‘components’?
Thank you