Fine-tuning Custom Model
Explore how to fine-tune custom image classification models in PyTorch by leveraging transfer learning. Learn to reuse pre-trained model weights for new tasks, manage training checkpoints, and handle optimizer states to efficiently enhance model performance without starting from scratch.
We'll cover the following...
We'll cover the following...
Instead of training a new image classification model from scratch, we can build on an existing model. This process is called fine-tuning a custom model. Fine-tuning is a method that applies transfer learning to repurpose a model for other tasks. It’s usually a lot cheaper and faster to fine-tune an existing model than to start over with a new one. For example, we can train an initial model for 10 classes with open-source ...