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Training open neural machine translation models
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Joerg Tiedemann 58690950b0 all models = opus
2020-01-15 23:18:07 +02:00
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finetune all models = opus 2020-01-15 23:18:07 +02:00
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Makefile all models = opus 2020-01-15 23:18:07 +02:00
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README.md

Train Opus-MT models

This package includes scripts for training NMT models using MarianNMT and OPUS data for OPUS-MT. More details are given in the Makefile but documentation needs to be improved. Also, the targets require a specific environment and right now only work well on the CSC HPC cluster in Finland.

Structure

Essential files for making new models:

  • Makefile: top-level makefile
  • Makefile.env: system-specific environment (now based on CSC machines)
  • Makefile.config: essential model configuration
  • Makefile.data: data pre-processing tasks
  • Makefile.doclevel: experimental document-level models
  • Makefile.tasks: tasks for training specific models and other things (this frequently changes)
  • Makefile.dist: make packages for distributing models (CSC ObjectStorage based)
  • Makefile.slurm: submit jobs with SLURM

Run this if you want to train a model, for example for translating English to French:

make SRCLANG=en TRGLANG=fr train

To evaluate the model with the automatically generated test data (from the Tatoeba corpus as a default) run:

make SRCLANG=en TRGLANG=fr eval

For multilingual (more than one language on either side) models run, for example:

make SRCLANG="de en" TRGLANG="fr es pt" train
make SRCLANG="de en" TRGLANG="fr es pt" eval

Note that data pre-processing should run on CPUs and training/testing on GPUs. To speed up things you can process data sets in parallel using the jobs flag of make, for example using 8 threads:

make -j 8 SRCLANG=en TRGLANG=fr data

Upload to Object Storage

swift upload OPUS-MT --changed --skip-identical name-of-file
swift post OPUS-MT --read-acl ".r:*"