bert-base-cased

BERT is a transformers model pretrained on a large corpus of English data in a self-supervised fashion . This model is case-sensitive: it makes a difference between English and English . It's mostly intended to be fine-tuned on downstream tasks that use the whole sentence (potentially masked)to make decisions, such as sequence classification, token classification or question answering . The team releasing BERT did not write a model card for this model so this model card has been written by the Hugging Face team . It was introduced in a paper and first released in the PePean repository . The model was pretrained with two objectives: Masked language modeling (MLM),