# UzBERT: pretraining a BERT model for Uzbek

Source: [UzBERT: pretraining a BERT model for Uzbek](<https://www.sota2.com/research/paper/68fa6a991e209131cea29430>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:29:26.390Z

Authors: B. Mansurov, A. Mansurov

Published: 2021-08-22T18:28:22.000Z

## Abstract

Pretrained language models based on the Transformer architecture have achieved state-of-the-art results in various natural language processing tasks such as part-of-speech tagging, named entity recognition, and question answering. However, no such monolingual model for the Uzbek language is publicly available. In this paper, we introduce UzBERT, a pretrained Uzbek language model based on the BERT architecture. Our model greatly outperforms multilingual BERT on masked language model accuracy. We make the model publicly available under the MIT open-source license.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2108.09814>)

[PDF](<https://arxiv.org/pdf/2108.09814.pdf>)