This assignment is due on Friday, February 14, 2020 before 01:30PM.

# Instructions

In this homework, you will be experiment with the ROCSTories dataset, which consists of 5-sentence long stories. You will build a few classifiers for the Story Cloze task. The task involves predicting which of two candidate 5th sentences best ends a story.

You should walk through the IPython Notebook here. It walks you through building a sentiment-based system for predicting the correct next ending as well as two neural network-based approaches that learn a classifier for the task.

You should create a writeup describing the experiments you conduct. We will be primarily grading you on this writeup, although you should also submit your code. Your writeup should include

• Your accuracy on the two validation sets and the 2016 test set using…
• A sentiment-based classifier
• A neural network trained only on the train set, as well as 2 variants.
• A neural network trained in a supervised way on the validation set, as well as 2 variants.
• Descriptions of your approaches for each of the above methods/variants. Try to make your descriptions detailed enough that another student could reimplement your approach from them.
• An error analysis:
• Find a couple examples your sentiment classifier gets wrong and discuss them.
• Are there any examples that all of your classifiers get wrong? What do you notice about them?

### What parameters can your vary?

Here are some ideas:

• The learning rate and optimizer
• The number of training steps
• The number of layers and types of activation functions in the model architecture
• The batch size
• For the supervised model that trains on the validation set, can you also incorporate the unlabeled training data?

# What to submit

• A file containing your writeup, as either report.pdf or report.md.
• Your modified IPython notebook as rocstories.ipynb.