Originally,<cite> Devlin et al. (2018)</cite> find that fine-tuning for three or four epochs works well for both small and large datasets alike. They also apply a generous MSL of 512, which may be unnecessary for document classification, where fewer tokens may suffice in determining the topic. Furthermore, while conducting our experiments, we find that even fine-tuning BERT is a computationally intensive task. We argue that it is important to study these two hyperparameters, as they are major determinants of the computational resources required to fine-tune BERT.