At a Glance

Name: Fine-tune a transformer-based neural network with PyTorch
Price: Free CAD
Rating: 4.7 (6 reviews)

Master the art of fine-tuning a transformer-based neural network using PyTorch. Discover the power of transfer learning as you meticulously fine-tune the entire neural network, comparing it to the more focused approach of fine-tuning just the final layer. Unlock this essential skill by immersing yourself in this captivating end-to-end hands-on project today!

A Look at the Project Ahead

Imagine you have a classification task, and you want to solve it using a transformer-based neural network model. Here are your options:

Train a model from scratch: One approach is to train a new model entirely from scratch. However, this method might not be the most effective. When you start from scratch, you miss out on the opportunity to benefit from transfer learning.
Fine-tune a pre-trained model: Transfer learning involves repurposing a pre-trained model that was initially trained for a different task. By fine-tuning this pre-trained model, you can adapt it to your specific classification task.

In this hands-on project, you will gain a comprehensive understanding of the entire end-to-end pipeline for fine-tuning a transformer-based neural network.

Learning objectives

Upon completion of this project, you have the ability to:

Define and pre-train a transformer-based neural network using PyTorch for a classification task.
Fully fine-tune the pre-trained model for a different classification task.
Compare results by fine-tuning only the last layer of the pre-trained model.

What You'll Need

For this project, you need an intermediate level of proficiency in Python, PyTorch, and deep learning. There’s no prerequisite for experience with or knowledge of LoRA. Additionally, the only equipment that you need is a computer equipped with a modern browser, such as the latest versions of Chrome, Edge, Firefox, or Safari.

Offered By: IBMSkillsNetwork

Fine-tune a transformer-based neural network with PyTorch

At a Glance

A Look at the Project Ahead

Learning objectives

What You'll Need