Training pipelines for Firefox Translations machine translation models.
The trained models are hosted in firefox-translations-models repository, compatible with bergamot-translator and power the Firefox web page translation starting with version 118.
The pipeline was originally developed as a part of Bergamot project that focuses on improving client-side machine translation in a web browser.
The pipeline is capable of training a translation model for a language pair end to end. Translation quality depends on the chosen datasets, data cleaning procedures and hyperparameters. Some settings, especially low resource languages might require extra tuning.
We use fast translation engine Marian.
You can find more details about the pipeline steps in the documentation.
An orchestrator is responsible for workflow management and parallelization.
- Taskcluster - Mozilla task execution framework. It is also used for Firefox CI. It provides access to the hybrid cloud workers (GCP + on-prem) with increased scalability and observability. Usage instructions.
- Snakemake - a file based orchestrator that allows to run the pipeline locally or on a Slurm cluster. Usage instructions. (The integration is not maintained since Mozilla has switched to Taskcluster. Contributions are welcome.)
Marian training metrics are parsed from logs and published using a custom module within the tracking directory.
More information is available here.
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High level overview post on Mozilla Hacks
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Model training guide - practical advice on how to use the pipeline
This project uses materials developed by:
- Bergamot project (github, website) that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825303
- HPLT project (github, website) that has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070350 and from UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee [grant number 10052546]
- OPUS-MT project (github, website)
- Many other open source projects and research papers (see References)