@ptrblck
After some further experimentation, I found that it doesn’t actually converge to 1. More specifically, it just learns very very slowly.
If when I start the training the loss is around 0.96. It drops only about 0.08 in 30,000 epochs.
I have been adjusting the learning rate as well as other hyperparameters. What steps can I take to improve how quickly the model learns?
I am Z scoring the data before training.
Yeah the model is quite small, I have since added a Tanh between tb two linear layers. How might I improve the model architecture?
I’m trying to solve a regression problem using a combination of continuous and categorical features.
Thank you so much for your help.