This is a fair point. The reason why I think "correlation" is a better metric than "predicts the exact correct score" is because of how I'll be using this model in the next post.

Broadly, the main use case for this model (in the RL context) will be to take two different versions of the same post, and predict which of the two is more likely to be upvoted. So what matters isn't that it gets the exact number of upvotes correctly, but that it correctly predicts the relative difference in likely upvote count between two variants.

Now it still doesn't do a great job at that (the correlation is only 0.53 after all) but it still does a good enough job to provide some useful signal.