Transfer Learning with a Pre-trained Model

medium (<1 hr) cnn transfer learning resnet fine-tuning

this month by E

Fine-tune a pre-trained model (e.g., resnet18 from torchvision.models) on a new, small image classification dataset (e.g., CIFAR-10). You'll need to freeze the weights of the initial layers and only train the final classification head. This is a classic transfer learning scenario where you leverage knowledge from a large dataset to solve a new task with limited data.

Verification: The model's accuracy on the new dataset should be significantly higher than a randomly initialized model trained for the same number of epochs, demonstrating the effectiveness of transfer learning. You should see a high accuracy on the validation set.