Tiny-Mud6713 OP t1_iwck8e1 wrote on November 14, 2022 at 5:18 PM

Reply to comment by Technical-Owl-6919 in [P] Need help with this CNN transfer learning problem by Tiny-Mud6713

The problem with efficient nets is that I ran a test on some models apriori, I got this graph, note that the dataset was ran for 3 epochs only each model.

https://drive.google.com/file/d/1OyXaWg6vMirYeI9zLSeGJ2v_qCz3msu4/view?usp=share_link

Technical-Owl-6919 t1_iwckvp7 wrote on November 14, 2022 at 5:22 PM

Something seems to be wrong, the validation scores should not be so low. Exactly what type of data are you dealing with ?

Tiny-Mud6713 OP t1_iwcleya wrote on November 14, 2022 at 5:25 PM

They're pictures of some plant, 8 classes for 8 different species of the same type of the plant.

Technical-Owl-6919 t1_iwclyq8 wrote on November 14, 2022 at 5:29 PM

So my friend, then you have to train the network from scratch, it is getting trapped into a local minima. Maybe a small network might help. Try training a ResNet15 or something similar from scratch. This has happened with me once, I was working with Simulation Images and could not get the AuC score to go above 0.92, once I trained it from scratch I got AUC scores close to 0.99, 0.98 etc.

Tiny-Mud6713 OP t1_iwcngla wrote on November 14, 2022 at 5:39 PM

So I import the model and unfreeze it immediately and just add my top layers ?

Technical-Owl-6919 t1_iwco8xr wrote on November 14, 2022 at 5:44 PM

Yes and train them, everything is unfrozen.

arg_max t1_iwcn3y0 wrote on November 14, 2022 at 5:36 PM

Imagenet 1k pretraining might not be the best for this as it contains few plant classes. The bigger in-21k has a much larger selection of plants and might be better suited for you. Timm has efficient net v2, beit, vit and convnext models pretrained on this though I don't use keras you might be able to find them for this framework.