Depends on your model - in the majority of cases training is a separate act from using the model, and just because you trained it doesn't mean it's well fitted.

Depends on your model - in the majority of cases training is a separate act from using the model, and just because you trained it doesn't mean it's well fitted. You end up caring about training speed because you don't know how many training runs you may have to do, grumpily fiddling with the model and hyperparameters after each training session trying to get a good model. Technically possible but probably not practical