basic:
  dataset: AirQuality
  device: cuda:0
  mode: train
  model: STAEFormer
  seed: 2023

data:
  batch_size: 16
  column_wise: false
  days_per_week: 7
  horizon: 24
  input_dim: 6
  lag: 24
  normalizer: std
  num_nodes: 35
  steps_per_day: 288
  test_ratio: 0.2
  val_ratio: 0.2

model:
  adaptive_embedding_dim: 80
  dow_embedding_dim: 24
  dropout: 0.1
  feed_forward_dim: 256
  in_steps: 24
  input_dim: 6
  input_embedding_dim: 24
  num_heads: 4
  num_layers: 3
  num_nodes: 35
  out_steps: 24
  output_dim: 6
  spatial_embedding_dim: 0
  steps_per_day: 24
  tod_embedding_dim: 24
  use_mixed_proj: true

train:
  batch_size: 16
  debug: false
  early_stop: true
  early_stop_patience: 15
  epochs: 100
  grad_norm: false
  log_step: 20000
  loss_func: mae
  lr_decay: false
  lr_decay_rate: 0.3
  lr_decay_step: 5,20,40,70
  lr_init: 0.003
  mae_thresh: 0.0
  mape_thresh: 0.0
  max_grad_norm: 5
  output_dim: 6
  plot: false
  real_value: true
  weight_decay: 0