PyTorch Sentiment Classifier From Scratch With Huggingface NLP Library - Full Tutorial

Learn to build a PyTorch sentiment classifier from scratch using the Huggingface NLP Library in this comprehensive tutorial video. Explore the process of combining Huggingface's NLP library with a BERT model from their Transformers library to create an IMDB sentiment classifier. Follow along as the instructor covers essential topics including boilerplate setup, PyTorch Lightning Module implementation, dataset loading, tokenization, working with Torch Tensors, creating a Data Loader, setting up a BERT model, and implementing validation and training steps. Gain practical insights through a detailed walkthrough, complete with code demonstrations and explanations. Access additional resources, including the instructor's GitHub repository, NLP Library documentation, and related tutorials, to further enhance your understanding of sentiment analysis using state-of-the-art NLP tools.

- Intro
- Boilerplate
- PyTorch Lightning Module
- Load Dataset
- Tokenization
- Torch Tensors
- Data Loader
- Create BERT Model
- Implement Validation and Train Step
- Run & Recap
- Epilogue