  This paper introduces a Scandinavian benchmarking platform, ScandEval, which
can benchmark any pretrained model on four different tasks in the Scandinavian
languages. The datasets used in two of the tasks, linguistic acceptability and
question answering, are new. We develop and release a Python package and
command-line interface, scandeval, which can benchmark any model that has been
uploaded to the Hugging Face Hub, with reproducible results. Using this
package, we benchmark more than 100 Scandinavian or multilingual models and
present the results of these in an interactive online leaderboard, as well as
provide an analysis of the results. The analysis shows that there is
substantial cross-lingual transfer among the Mainland Scandinavian languages
(Danish, Swedish and Norwegian), with limited cross-lingual transfer between
the group of Mainland Scandinavian languages and the group of Insular
Scandinavian languages (Icelandic and Faroese). The benchmarking results also
show that the investment in language technology in Norway, Sweden and Denmark
has led to language models that outperform massively multilingual models such
as XLM-RoBERTa and mDeBERTaV3. We release the source code for both the package
and leaderboard.
