Hey, I just installed and played around with reactionRNN; I hate to be negative (especially to people open sourcing models, kudos!), but your model seems to perform quite poorly. It immediately failed my "easy" smell tests: https://i.imgur.com/FvfuZgy.png, and didn't really work on most of my other tests: "This book sucks" is 0% angry, "I'm going to go home and listen to emo music and cry" is 0% sad, "Check out this hilarious youtube video" is only 26% haha. Your example "He was only 41." is 100% sad, but "He was only 42." is 0% sad. These aren't hand-picked, these are literally things I just typed in. From what I can tell it usually gets anything negative wrong, and usually picks "haha" for the positive ones.

Subjective performance is worse than your included examples. I've been building models my whole career, and what I've learned is most people will take claimed performance at face value until it burns them. It's beneficial to no one if someone comes up with an idea based off your repo description, builds it out, then finds it doesn't work adequately. My advice is to update your examples and test cases, and keep finding ways to improve the model.