What are the common challenges in training transformer models?

What are the common challenges in training transformer models?

Some common challenges include overfitting, high computational costs, and the need for large datasets.

How can I mitigate overfitting when training transformers?

You can use techniques like dropout, data augmentation, and early stopping to help mitigate overfitting.

What are the best practices for optimizing training time?

Best practices include using mixed precision training, distributed training, and efficient data loading.

Are there specific datasets recommended for training transformers?

Yes, datasets like the Common Crawl, Wikipedia, and various domain-specific corpora are commonly used.