IFT6759: Low Resource Machine Translation

This project was created as part of the UdeM course IFT6759 (https://admission.umontreal.ca/cours-et-horaires/cours/IFT-6759/). The objective of this project is to predict French translations of English sentences in a low-resource setting. Refer to the report and presentation included in this repository for more details.

Steps to run evaluation:

1. Go to scripts folder
2. Edit run_evaluator_script.sh. Change the --input-file-path and --target-file-path as required
3. Submit batch job: Run sbatch run_evaluator_script.sh from inside scripts folder

• As we had small aligned dataset of 11k examples, we decided to use single-fold validation held out strategy.

To setup a new local environment:

module load python/3.7
virtualenv ../local_env
source ../local_env/bin/activate
pip install -r requirements_local.txt

TODO:

• Add beam search
• Label Smoothing
• Run more back-translation iteration