Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Transformers

You're reading from   Mastering Transformers Build state-of-the-art models from scratch with advanced natural language processing techniques

Arrow left icon
Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801077651
Length 374 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Savaş Yıldırım Savaş Yıldırım
Author Profile Icon Savaş Yıldırım
Savaş Yıldırım
Meysam Asgari- Chenaghlu Meysam Asgari- Chenaghlu
Author Profile Icon Meysam Asgari- Chenaghlu
Meysam Asgari- Chenaghlu
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction – Recent Developments in the Field, Installations, and Hello World Applications
2. Chapter 1: From Bag-of-Words to the Transformer FREE CHAPTER 3. Chapter 2: A Hands-On Introduction to the Subject 4. Section 2: Transformer Models – From Autoencoding to Autoregressive Models
5. Chapter 3: Autoencoding Language Models 6. Chapter 4:Autoregressive and Other Language Models 7. Chapter 5: Fine-Tuning Language Models for Text Classification 8. Chapter 6: Fine-Tuning Language Models for Token Classification 9. Chapter 7: Text Representation 10. Section 3: Advanced Topics
11. Chapter 8: Working with Efficient Transformers 12. Chapter 9:Cross-Lingual and Multilingual Language Modeling 13. Chapter 10: Serving Transformer Models 14. Chapter 11: Attention Visualization and Experiment Tracking 15. Other Books You May Enjoy

Utilizing run_glue.py to fine-tune the models

So far, we have designed a fine-tuning architecture from scratch using both native PyTorch and the Trainer class. The HuggingFace community also provides another powerful script called run_glue.py for GLUE benchmark and GLUE-like classification downstream tasks. This script can handle and organize the entire training/validation process for us. If you want to do quick prototyping, you should use this script. It can fine-tune any pre-trained models on the HuggingFace hub. We can also feed it with our own data in any format.

Please go to the following link to access the script and to learn more: https://github.com/huggingface/transformers/tree/master/examples.

The script can perform nine different GLUE tasks. With the script, we can do everything that we have done with the Trainer class so far. The task name could be one of the following GLUE tasks: cola, sst2, mrpc, stsb, qqp, mnli, qnli, rte, or wnli.

Here is the script scheme for...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image