Use FScore (Macro) as monitor metric instead of accuracy for Classification Task [FEATURE]

[jtbai]

When training for a classification task, FScore is more relevant than accuracy. After training, when I select the best model, I often get a subpar model, since a bette model with higher FScore may be available, and no checkpoint were log for it

Either use FScore as default monitor metric for classification or additionnal task such as "unbalanced_classification".

At the moment I have to manually add the FScore Macro and max as monitor mode. Very easy to fix - I just don't see why someone with a normal classification task would select accuracy over FScore as target metric.