Is it possible to change the loss function dynamically during training?
You have to implement your own algorithm. This is mostly possible with Tensorflow.
I am working on a machine learning project and I am wondering whether it is possible to change the loss function while the network is training. I'm not sure how to do it exactly in code.
For example, start training with cross entropy loss and then halfway through training, switch to 0-1 loss.