Nice work! I was wondering if you noticed changes in the output coherence during training?

I fine-tuned it on the corpus of The Office quotes [1] and I noticed that a loss of around 0.9 gives me the most 'humorous' outputs. This may be subjective but I think for comedy the surprise plays a huge role and for longer training (and loss around 0.4) it feels overly unsurprising and therefore less funny. I also tried sampling with temperatures >1 but then it just goes crazy (e.g. some outputs are completely in Latin).

[1] https://www.reddit.com/r/MachineLearning/comments/bmn0og/p_l...