Design of an Open-Source Architecture for Neural Machine Translation
Séamus Lankford Haithem Afli Andy Way
adaptNMT is an open-source application that offers a streamlined approach to
the development and deployment of Recurrent Neural Networks and Transformer
models. This application is built upon the widely-adopted OpenNMT ecosystem,
and is particularly useful for new entrants to the field, as it simplifies the
setup of the development environment and creation of train, validation, and
test splits. The application offers a graphing feature that illustrates the
progress of model training, and employs SentencePiece for creating subword
segmentation models. Furthermore, the application provides an intuitive user
interface that facilitates hyperparameter customization. Notably, a
single-click model development approach has been implemented, and models
developed by adaptNMT can be evaluated using a range of metrics. To encourage
eco-friendly research, adaptNMT incorporates a green report that flags the
power consumption and kgCO${_2}$ emissions generated during model development.
The application is freely available.