Since there are so many lines of code and files, I felt it was a little difficult to follow along while you were proceeding by simply copying things. Still, the content was so informative and covered a topic I had never heard of before that I think I was able to tolerate those shortcomings. In particular, since the model used for evaluation cannot be trusted either, that model also needs to be evaluated. But if another model evaluates it again, then ultimately it becomes impossible to trust it. Understanding it from that perspective, I think the conclusion of model evaluation is that humans have to put in the hard work. - In fact, I understand that Meta hired more people and used more human labor to give tasks to and train models, and it seems that perspective is reflected here as well.