Hey man, thanks! I didn't try to filter to any subgenres, but I did try to give the model as easy a time as possible by trying to stick verses which stuck to the most common words (lowering the perplexity of the corpus). I would call this genre 'mediocre', and may explain why I had such a hard time with the sexism thing.
Internal rhyming / assonance and other stuff could be done by rewarding the model for using it during the beam search. I suspect it's going to be hard to tune how to set the reward so it still makes sense, it only just makes sense already. I also think at this point you would really need to sit down and figure out what rhymes and what doesn't. I did the quickest, hackiest thing I could think of, which was good enough for generating end rhymes, but if you want to have internal rhymes and not massively constrain the model, I think you need to work it out purely from analysing the syllables.
Internal rhyming / assonance and other stuff could be done by rewarding the model for using it during the beam search. I suspect it's going to be hard to tune how to set the reward so it still makes sense, it only just makes sense already. I also think at this point you would really need to sit down and figure out what rhymes and what doesn't. I did the quickest, hackiest thing I could think of, which was good enough for generating end rhymes, but if you want to have internal rhymes and not massively constrain the model, I think you need to work it out purely from analysing the syllables.