reddit classification and generation experiments on the reddit dataset

Steps for training:

1: clean up the data with make_data.py which creates a new csv.

2: if there are pretrained embeddings, run the new csv through filter embeddings to create embedding matrix. make sure to have the same parameters on this file, and the model.

3: now, it is ready to train. you can train the auto encoder, or the classifier. it saves the model which is the same for both, so it is possible to train the auto encoder, and then train that model for classification. Of course the models can be trained multiple times for the same thing. Be weary, because the hyperparameters must be the same in order for you to do this.