Day 17

Working with the ladder network all day has brought some things to light. Firstly, and most importantly, the model is overfitting like there is no tomorrow. This means that the model memorizes the training data instead of generalizing. Contrary to what high school has taught me, this is undesired. The original model predicts up to 15% more accurately on training data than validation data which is very bad. I've been trying to change parameters to reduce this margin, but I haven't had much success. The main problem is that there are way too many knobs to turn. I could add layers, remove layers, change the sizes of layers, adjust the amount of noise, change weights of costs, change the initial learning rate, change the learning rate function, or change the optimizer. Decisions, decisions.

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