HooshvareLab/bert-base-parsbert-armanner-uncased

ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base . The models (downstream tasks) are uncased and trained with whole word masking . This task aims to extract named entities in the text, such as names and labels with appropriate NER classes such as locations, organizations, etc. The datasets used for this task contain sentences that are marked with IOB format . In this format, tokens that are not part of an entity are tagged as ”O” the ”B”tag corresponds to the first word of an object, and the . ”I” tag corresponds to,