# nmt.yaml #Basic configuration file. You can add any arguments that would be passed via flags, as # described here: https://opennmt.net/OpenNMT-py/ . You can play with different models # the framework allows you to specify. #Fill in TODOs in order to have a minimal complete yaml file ## Where the samples will be written save_data: #TODO: prefix for saving files ## Where the vocab(s) will be written src_vocab: #TODO: vocabulary file for source tgt_vocab: #TODO: vocubulary file to target # Prevent overwriting existing files in the folder overwrite: False # Corpus paths data: corpus_1: path_src: #TODO source train file path_tgt: #TODO target train file valid: path_src: #TODO source dev file path_tgt: #TDOO target dev file # Train on a single GPU # optimzer hyper-paramenters world_size: 1 gpu_ranks: [0] learning_rate: 1 start_decay_steps : 50000 # Where to save the checkpoints save_model: # TODO prefix for saivng models save_checkpoint_steps: 10000 train_steps: 100000 valid_steps: 500 #model parameters layers: 2