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What is BERT Model Implementation in Colab about?

This document summarizes the steps taken to build and train a BERT model for text classification on a SMS spam detection dataset. The key steps include: 1. Preprocessing the SMS spam dataset and splitting it into train, validation and test sets. 2. Loading the pre-trained BERT model and defining a classification architecture with additional layers. 3. Tokenizing and encoding the train, validation and test texts using the BERT tokenizer. 4. Defining the model, loss function, optimizer and training loop

Author

mehtakinjalb

Language

EN