OpusCleaner and OpusTrainer, open source toolkits for training Machine Translation and Large language models
Abstract
Developing high quality machine translation systems is a labour intensive, challenging and confusing process for newcomers to the field. We present a pair of tools OpusCleaner and OpusTrainer that aim to simplify the process, reduce the amount of work and lower the entry barrier for newcomers. OpusCleaner is a data downloading, cleaning, and proprocessing toolkit. It is designed to allow researchers to quickly download, visualise and preprocess bilingual (or monolingual) data that comes from many different sources, each of them with different quality, issues, and unique filtering/preprocessing requirements. OpusTrainer is a data scheduling and data augmenting tool aimed at building large scale, robust machine translation systems and large language models. It features deterministic data mixing from many different sources, on-the-fly data augmentation and more. Using these tools, we showcase how we can use it to create high quality machine translation model robust to noisy user input; multilingual models and terminology aware models.
Cite
@article{arxiv.2311.14838,
title = {OpusCleaner and OpusTrainer, open source toolkits for training Machine Translation and Large language models},
author = {Nikolay Bogoychev and Jelmer van der Linde and Graeme Nail and Barry Haddow and Jaume Zaragoza-Bernabeu and Gema Ramírez-Sánchez and Lukas Weymann and Tudor Nicolae Mateiu and Jindřich Helcl and Mikko Aulamo},
journal= {arXiv preprint arXiv:2311.14838},
year = {2023}
}
Comments
Code on Github: https://github.com/hplt-project/OpusCleaner and https://github.com/hplt-project/OpusTrainer