seed: 42
data:
  format_version: clm5_emulator_v1
  path: data/clm5_ppe.npz
  samples: 40
  grid: [46, 72]
  input_parameters: 6
  targets: [GPP, LHF]
  eof_modes: 3
model:
  hidden_dim: 12
train:
  epochs: 4
  batch_size: 10
  learning_rate: 0.005
  weight_decay: 0.0001
paths:
  checkpoint: result/checkpoints/clm5_emulator.pt
  training_metrics: result/training/metrics.json
  predictions: result/output/predictions.npz
  evaluation: result/evaluation/metrics.json
  figure: result/evaluation/comparison.png
paper_model:
  ppe_members: 100
  input_parameters: [medlynslope, dleaf, kmax, fff, dint, baseflow_scalar]
  hidden_layers: 2
  hidden_candidates: [5, 15]
  optimizer: RMSprop
  learning_rate: 0.005
  batch_size: 30
  split: [0.6, 0.2, 0.2]