patchtst.yaml

# lightning==2.3.0.dev0
seed_everything: 1
trainer:
  accelerator: gpu
  devices: 1
  strategy: auto
  max_epochs: 50
  use_distributed_sampler: false
  limit_train_batches: 100
  log_every_n_steps: 1
  default_root_dir: ./results
  accumulate_grad_batches: 1
model:
  forecaster:
    class_path: probts.model.forecaster.point_forecaster.PatchTST
    init_args:
      stride: 3
      patch_len: 6
      dropout: 0.1
      f_hidden_size: 32
      n_layers: 3
      n_heads: 8
      fc_dropout: 0.2
      head_dropout: 0
      individual: false
  optimizer_config:
    class_name: torch.optim.Adam
    init_args:
      weight_decay: 0
  lr_scheduler_config:
    class_name: torch.optim.lr_scheduler.OneCycleLR
    init_args:
      max_lr: 0.0001
      steps_per_epoch: 100
      pct_start: 0.3
      epochs: 50
  learning_rate: 0.0001
  quantiles_num: 20
data:
  data_manager:
    class_path: probts.data.data_manager.DataManager
    init_args:
      dataset: exchange_rate_nips
      split_val: true
      scaler: standard # identity, standard, temporal
  batch_size: 64
  test_batch_size: 64
  num_workers: 8