  We present bgGLUE(Bulgarian General Language Understanding Evaluation), a
benchmark for evaluating language models on Natural Language Understanding
(NLU) tasks in Bulgarian. Our benchmark includes NLU tasks targeting a variety
of NLP problems (e.g., natural language inference, fact-checking, named entity
recognition, sentiment analysis, question answering, etc.) and machine learning
tasks (sequence labeling, document-level classification, and regression). We
run the first systematic evaluation of pre-trained language models for
Bulgarian, comparing and contrasting results across the nine tasks in the
benchmark. The evaluation results show strong performance on sequence labeling
tasks, but there is a lot of room for improvement for tasks that require more
complex reasoning. We make bgGLUE publicly available together with the
fine-tuning and the evaluation code, as well as a public leaderboard at
https://bgglue.github.io/, and we hope that it will enable further advancements
in developing NLU models for Bulgarian.

Computation and Language;Information Retrieval;Machine Learning