Model YAML configurations

Before training, you must select the model configuration you wish to train. Please refer to the key features for a description of the options available, as well as the training times. Having selected a configuration it is necessary to note the config path and sentencepiece vocabulary size ("spm size") of your chosen config from the following table as these will be needed in the subsequent data preparation steps:

NameParametersspm sizeconfigAcceleration supported?
testing49M1023testing-1023sp.yaml✔
base85M8703base-8703sp.yaml✔
large196M17407large-17407sp.yaml✔

The testing configuration is included because it is quicker to train than either base or large. It is recommended to train the testing model on LibriSpeech as described here before training base or large on your own data.

Note

The testing config is not recommended for production use. Unlike the testing config, the base and large configs were optimized to provide a good tradeoff between WER and throughput on the accelerator. The testing config will currently run on the accelerator, but this is deprecated. Support for this may be removed in future releases.

Missing YAML fields

The configs referenced above are not intended to be edited directly. Instead, they are used as templates to create <config-name>_run.yaml files. The _run.yaml file is a copy of the chosen config with the following fields populated:

  • sentpiece_model: /datasets/sentencepieces/SENTENCEPIECE.model
  • stats_path: /datasets/stats/STATS_SUBDIR
  • max_duration: MAX_DURATION
  • ngram_path: /datasets/ngrams/NGRAM_SUBDIR

Populating these fields can be performed by the training/scripts/create_config_set_env.sh script.

For example usage, see the following documentation: Prepare LibriSpeech in the JSON format.