The train subcommand can be used to train a model. It requires a configuration file and a directory in which to write the results.

$ allennlp train --help
 usage: allennlp train [-h] -s SERIALIZATION_DIR [-r] [-f] [-o OVERRIDES]
                       [--cache-directory CACHE_DIRECTORY]
                       [--cache-prefix CACHE_PREFIX]
                       [--include-package INCLUDE_PACKAGE]

 Train the specified model on the specified dataset.

 positional arguments:
   param_path            path to parameter file describing the model to be

 optional arguments:
   -h, --help            show this help message and exit
                         directory in which to save the model and its logs
   -r, --recover         recover training from the state in serialization_dir
   -f, --force           overwrite the output directory if it exists
   -o OVERRIDES, --overrides OVERRIDES
                         a JSON structure used to override the experiment
                         outputs tqdm status on separate lines and slows tqdm
                         refresh rate
   --cache-directory CACHE_DIRECTORY
                         Location to store cache of data preprocessing
   --cache-prefix CACHE_PREFIX
                         Prefix to use for data caching, giving current
                         parameter settings a name in the cache, instead of
                         computing a hash
   --include-package INCLUDE_PACKAGE
                         additional packages to include