Unsupervised and Self-Supervised Pretraining

Next, let's focus on a crucial aspect of transformers—unsupervised and self-supervised pretraining. This aspect is especially significant as we navigate the complexities of training a massive model.

Scalability to learn from a large dataset

A key advantage of transformers is their scalability when learning from a large dataset. Unlike convolutional or recurrent models, transformers operate without making strong assumptions about the problem's structure, allowing them to handle diverse datasets effectively.