Building an Entity Extraction Model Using BERT

Learn how to build an entity extraction model using BERT in this comprehensive video tutorial. Explore the process of creating an entity extraction model using the Hugging Face Transformers library and PyTorch. Follow along as the instructor demonstrates the entire workflow, from dataset preparation and configuration to training and prediction. Gain insights into key concepts such as data loading, tokenization, loss calculation, and model output. Discover best practices for implementing BERT-based entity extraction models that can be applied to various domains. By the end of this tutorial, acquire the skills to develop your own custom entity extraction models for diverse natural language processing tasks.

Introduction
Dataset
Config
Data Loader
Tokenizer
Training
Coding
Loss
Output
Code
Metadata
Entity Model
Best Loss
Prediction