fairseq/examples/discriminative_reranking_nmt/config/deen.yaml

# @package _group_

common:
  fp16: true
  log_format: json
  log_interval: 50
  seed: 2

checkpoint:
  no_epoch_checkpoints: true
  best_checkpoint_metric: bleu
  maximize_best_checkpoint_metric: true

task:
  _name: discriminative_reranking_nmt
  data: ???
  num_data_splits: ???
  include_src: true
  mt_beam: 50
  eval_target_metric: true
  target_metric: bleu

dataset:
  batch_size: 50
  num_workers: 6
  required_batch_size_multiple: 50
  valid_subset: ???

criterion:
  _name: kl_divergence_rereanking
  target_dist_norm: minmax
  temperature: 0.5

optimization:
  max_epoch: 200
  lr: [0.00005]
  update_freq: [32]

optimizer:
  _name: adam
  adam_betas: (0.9,0.98)
  adam_eps: 1e-06

lr_scheduler:
  _name: polynomial_decay
  warmup_updates: 8000
  total_num_update: 320000

model:
  _name: discriminative_nmt_reranker
  pretrained_model: ???
  classifier_dropout: 0.2

distributed_training:
  ddp_backend: no_c10d
  distributed_world_size: 16