1.1 KiB
1.1 KiB
| title | date | draft |
|---|---|---|
| Week 6 | 2022-03-13T12:40:17+01:00 | false |
This week I finished programming the basic CNN model using transfer learning. I decided to train it for 20 epochs to make sure there weren't any runtime errors in my code. As I don't own an Nvidia GPU (I have an AMD GPU), I couldn't make use of the pytorch version that utilised CUDA to speed up processing. There is a RocM version of pytorch for AMD GPUs1 but RocM isn't as mature as CUDA and only officially supports a small subset of Linux distributions. Therefore, for this model I trained on the COU for only 20 epochs just to make sure it ran successfully before trying to find some Nvidia compute.
Transfer learning model architecture
Full
Simplified
Validation and train loss over 20 epochs
