Using pos_weight in BCEWithLogitsLoss to optimize for F2 score

I have a multi-class multi-label classification problem, and so I’ve been using the 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 in pos_weight to be able to do this?