I tried your notebook, the maximal accuracy I can get using standard resnet50 (Learner and without tns-net) is 90.12%. The max accuracy with TNS-Net is 93.91, that means a respectable improvement comparing to pure resnet50 Learner. But if I use the same resnet50 with cnn-learner, I can get easily 95.26%. People can get also 96.4% using resnet50 with cnn-learner according to Lesson-1-pets Benchmarks
Hopefully, if we can use cnn-learner with TNS-Net, we can improve the current “possible maximal accuracy” again.
If I am not mistaken, the difference of model created by cnn-learner and Learner is just about the custom head, isn’t it?
Here is once again the comparison in a table:
| Leaner only | Learner + TNS-Net | cnn-learner (mine) | cnn-learner (pets-benchmarks) |
|---|---|---|---|
| 90.12 | 93.91 | 95.26 | 96.40 |