Masked Language Modelling

Masked Language Modelling (MLM) is a language model training technique where certain words in a sentence are masked, and the model is trained to predict the missing tokens based on the surrounding context. This approach allows models like BERT to capture bidirectional context, improving their performance on various tasks such as question-answering and text classification. Despite its benefits, MLM requires significant computational resources and has limitations in processing long sequences.