# Using pos_weight to improve recall in a multi-class multi-label problem

I have a multi-label classification problem, and so I’ve been using the Pytorch's BCEWithLogitsLoss. I’d like to optimize my model for a higher F2 score, and so want to bias it to have greater recall (with decent precision too of course). Are there any guidelines for setting the values of pos_weight to be able to do this?