Code for the MBART QE Estimator (M2) from IST-Unbabel 2021 Submission for the Quality Estimation Shared Task
For XLMR Estimators (M1) please take a look at OpenKiwi
@inproceedings{Zerva-etal-2021-ist,
title = {{IST-Unbabel 2021 Submission for the Quality Estimation Shared Task}},
author = {Zerva, Chrysoula and van Stigt, Daan and Rei, Ricardo and C Farinha, Ana and Souza, José G. C. de and Glushkova, Taisiya and Vera, Miguel and Kepler, Fabio and Martins, André},
year = 2021,
month = nov,
booktitle = {Proceedings of the Sixth Conference on Machine Translation},
publisher = {Association for Computational Linguistics},
address = {Online},
}
pip install -r requirements.txt
pip install -e .
Download the MLQE-PE with Glass-Box features:
cd data
wget https://unbabel-experimental-data-sets.s3.eu-west-1.amazonaws.com/wmt21/glassbox-MLQE-PE.tar.gz
tar -xf glassbox-MLQE-PE.tar.gz
NOTE: If you use this data please cite the original MLQE-PE corpus!
python cli.py train -f configs/mbart50-m2m.yaml
python cli.py search -f configs/mbart50-m2m.yaml
python evaluate.py --checkpoint {path/to/checkpoint}.ckpt