OpusCleaner and OpusTrainer, open source toolkits for training Machine Translation and Large language models

TL;DR

This paper introduces OpusCleaner and OpusTrainer, open source tools that simplify data preparation and training for machine translation and large language models, making the process more accessible and efficient.

Contribution

The paper presents two novel open source toolkits that streamline data cleaning, preprocessing, augmentation, and training for multilingual and robust language models.

Findings

Enabled creation of high-quality machine translation models

Demonstrated robustness to noisy user input

Supported multilingual and terminology-aware 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.