  This project aims to produce the next volume of machine-generated poetry, a
complex art form that can be structured and unstructured, and carries depth in
the meaning between the lines. GPoeT-2 is based on fine-tuning a state of the
art natural language model (i.e. GPT-2) to generate limericks, typically
humorous structured poems consisting of five lines with a AABBA rhyming scheme.
With a two-stage generation system utilizing both forward and reverse language
modeling, GPoeT-2 is capable of freely generating limericks in diverse topics
while following the rhyming structure without any seed phrase or a posteriori
constraints.Based on the automated generation process, we explore a wide
variety of evaluation metrics to quantify "good poetry," including syntactical
correctness, lexical diversity, and subject continuity. Finally, we present a
collection of 94 categorized limericks that rank highly on the explored "good
poetry" metrics to provoke human creativity.
