  Style transfer is the task of automatically transforming a piece of text in
one particular style into another. A major barrier to progress in this field
has been a lack of training and evaluation datasets, as well as benchmarks and
automatic metrics. In this work, we create the largest corpus for a particular
stylistic transfer (formality) and show that techniques from the machine
translation community can serve as strong baselines for future work. We also
discuss challenges of using automatic metrics.
