find-lr subcommand can be used to find a good learning rate for a model.
It requires a configuration file and a directory in
which to write the results.
$ allennlp find-lr --help usage: allennlp find-lr [-h] -s SERIALIZATION_DIR [-o OVERRIDES] [--start-lr START_LR] [--end-lr END_LR] [--num-batches NUM_BATCHES] [--linear] [--stopping-factor STOPPING_FACTOR] [--linear] [--include-package INCLUDE_PACKAGE] param_path Find a learning rate range where the loss decreases quickly for the specified model and dataset. positional arguments: param_path path to parameter file describing the model to be trained optional arguments: -h, --help show this help message and exit -s SERIALIZATION_DIR, --serialization-dir SERIALIZATION_DIR directory in which to save Learning rate vs loss -f, --force overwrite the output directory if it exists -o OVERRIDES, --overrides OVERRIDES a JSON structure used to override the experiment configuration. --start-lr START_LR learning rate to start the search. --end-lr END_LR learning rate up to which search is done. --num-batches NUM_BATCHES number of mini-batches to run Learning rate finder. --stopping-factor STOPPING_FACTOR stop the search when the current loss exceeds the best loss recorded by multiple of stopping factor --linear increase learning rate linearly instead of exponential increase --include-package INCLUDE_PACKAGE additional packages to include