  We provide a comprehensive investigation of different custom and
off-the-shelf architectures as well as different approaches to generating
feature vectors for offensive language detection. We also show that these
approaches work well on small and noisy datasets such as on the Offensive
Language Identification Dataset (OLID), so it should be possible to use them
for other applications.
