experiment: FluxNet-ShallowWater-LAP-pushforward
paper: https://arxiv.org/pdf/2602.01941v2
seed: 42
data:
  root: ./data
  fields: [h, mx, my]
  shape: [64, 64]
  dt: 0.04
  expected_counts: {train: 50, val: 20, test: 50, test_long: 50}
  expected_frames: {train: 61, val: 61, test: 61, test_long: 121}
  normalization: none
  reference_negative_tolerance: 1.0e-9
model:
  base_channels: 64
  num_blocks: 6
  kernel_size: 5
  neighborhood_size: 3
  epsilon: 1.0e-6
training:
  epochs: 300
  pushforward_steps: 5
  batch_size: 16
  num_workers: 4
  optimizer: AdamW
  learning_rate: 1.0e-3
  weight_decay: 1.0e-2
  scheduler: ReduceLROnPlateau
  scheduler_factor: 0.5
  scheduler_patience: 15
  loss: mse_step1_plus_mse_step5
  early_stopping: false
  gradient_clip: null
  precision: float32
  print_every_batches: 10
  checkpoint_every_epochs: 10
evaluation:
  batch_size: 10
  long_test_every_epochs: 50
  splits: [test, test_long]
  example_cases: [A1, A2, B1, B2]
paths:
  best_checkpoint: weight/best_model.pth
  last_checkpoint: weight/last_model.pth
  results: results