config.yaml

fit:
  seed_everything: 7

  trainer:
    enable_checkpointing: true
    callbacks:
      - class_path: pytorch_lightning.callbacks.LearningRateMonitor
        init_args:
          logging_interval: epoch
      - class_path: pytorch_lightning.callbacks.ModelCheckpoint
        init_args:
          save_top_k: 1
          monitor: val_ExpRate
          mode: max
          filename: '{epoch}-{step}-{val_ExpRate:.4f}'
    # accelerator: 'cpu'
    # fast_dev_run: True
    accelerator: 'gpu'
    devices: 0, 1
    strategy:
      class_path: pytorch_lightning.strategies.ddp.DDPStrategy
      init_args:
        find_unused_parameters: False
    check_val_every_n_epoch: 2
    max_epochs: 300
    deterministic: true
  model:
    d_model: 256
    # encoder
    growth_rate: 24
    num_layers: 16
    # decoder
    nhead: 8
    num_decoder_layers: 3
    dim_feedforward: 1024
    dropout: 0.3
    dc: 32
    cross_coverage: true
    self_coverage: true
    # beam search
    beam_size: 10
    max_len: 200
    alpha: 1.0
    early_stopping: false
    temperature: 1.0
    # training
    learning_rate: 0.08
    patience: 20
  data:
    zipfile_path: data.zip
    test_year: "2019"
    train_batch_size: 8
    eval_batch_size: 4
    num_workers: 5
    scale_aug: true