bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark

Momchil Hardalov, Pepa Atanasova, Todor Mihaylov, Galia Angelova, Kiril Simov +5 more
6/4/2023
cs.CLcs.IRcs.LG

No official code found. Best implementation: bgGLUE/bgglue (8 stars, MIT, last commit 2023-08-06).

Abstract

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.

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Code Implementations(1)

bgGLUE/bgglueCommunity100%
MIT

bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark

80Shell, PythonMay 7, 20233 years agoMIT

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Cite this paper

@article{hardalov2023bgglue,
  title  = {bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark},
  author = {Momchil Hardalov and Pepa Atanasova and Todor Mihaylov and Galia Angelova and Kiril Simov and Petya Osenova and Ves Stoyanov and Ivan Koychev and Preslav Nakov and Dragomir Radev},
  year   = {2023},
  eprint = {2306.02349},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.02349v2}
}

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