Closed 3 days ago.

I’ve been playing with this music genre classifier ( https://github.com/musikalkemist/DeepLearningForAudioWithPython/blob/master/13-%20Implementing%20a%20neural%20network%20for%20music%20genre%20classification/code/mlp_genre_classifier.py ) and been trying to improve the model accuracy, which currently is only about 60%. I’ve tried changing the network architecture by adding an additional hidden layer, used different values for the dropout but that didn’t help. I’ve also experimented with different values for the learning rate but that too didn’t help.

I am trying to use an already trained model to transfer the learning to a model I will create and modifying only the last few layers. The goal of this is to used the already trained model (trained on millions of images already) to help my model classify food item recognition. I am pretty new to Keras and I am facing an issue that I am now starting understand to but don’t know how to resolve