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This article is divided into two parts; they are: • Architecture and Training of BERT • Variations of BERT BERT is an encoder-only model.

This article is divided into four parts; they are: • Preparing Documents • Creating Sentence Pairs from Document • Masking Tokens • Saving the Training Data for Reuse Unlike decoder-only models, BERT’s pretraining is more complex.

Machine learning models often behave differently across environments.

Clustering models in machine learning must be assessed by how well they separate data into meaningful groups with distinctive characteristics.