  Automated Machine Learning (AutoML) has gained increasing success on tabular
data in recent years. However, processing unstructured data like text is a
challenge and not widely supported by open-source AutoML tools. This work
compares three manually created text representations and text embeddings
automatically created by AutoML tools. Our benchmark includes four popular
open-source AutoML tools and eight datasets for text classification purposes.
The results show that straightforward text representations perform better than
AutoML tools with automatically created text embeddings.
