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A short tutorial on performing fine tuning or transfer learning in PyTorch.
| Date | Stars |
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| 2026-07-24 | 290 |
| 2026-07-25 | 290 |
| 2026-07-28 | 290 |
| 2026-07-30 | 290 |
| 2026-07-31 | 290 |
| 2026-08-06 | 290 |
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  # Pytorch Tutorial for Fine Tuning/Transfer Learning a Resnet for Image Classification If you want to do image classification by fine tuning a pretrained mdoel, this is a tutorial will help you out. It shows how to perform fine tuning or transfer learning in PyTorch with your own data. It is based on a bunch of of official pytorch tutorials/examples. I felt that it was not exactly super trivial to perform in PyTorch, and so I thought I'd release my code as a tutorial which I wrote originally for my research. Highly encourage you to run this on a new data set (read main_fine_tuning.py to know which format to store your data in), but for a sample dataset to start with, you can download a simple 2 class dataset from here - https://download.pytorch.org/tutorial/hymenoptera_data.zip All Torch and PyTorch specific details have been explained in detail in the file main_fine_tuning.py Hope this tutorial helps you out! :) Credits - This tutorial is built on top of mainly on 2 Pytorch tutorials - http://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html and https://github.com/pytorch/examples/tree/master/imagenet.
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matched fp:ee50249820e6f9fa, name:fine-tuning, desc:fine-tuning, readme:fine-tuning
matched fp:ee50249820e6f9fa, topic:deep-learning
matched fp:ee50249820e6f9fa, topic:image-classification, readme:image classification
matched fp:ee50249820e6f9fa, topic:tutorial, name:tutorial, desc:tutorial