seed: 42
data:
  root: data
  protocol: synthetic_multiscale_geospatial_rgb
  input_size: 16
  target_size: 32
  channels: 3
  num_classes: 4
  train_samples: 40
  test_samples: 16
  gsd_values: [0.5, 1.0, 2.0, 4.0]
model:
  input_size: 16
  target_size: 32
  patch_size: 4
  in_channels: 3
  embed_dim: 64
  encoder_depth: 2
  encoder_heads: 4
  decoder_dim: 48
  decoder_depth: 1
  decoder_heads: 4
  mask_ratio: 0.75
  reference_gsd: 1.0
  blur_kernel: 5
  band_config:
    low: {kernel: 5, target: low_frequency}
    high: {residual: true, target: high_frequency}
training:
  epochs: 3
  batch_size: 8
  learning_rate: 0.0005
  weight_decay: 0.05
  num_workers: 0
  gradient_accumulation: 1
  amp: true
  warmup_fraction: 0.1
runtime:
  device: auto
paths:
  checkpoint: result/checkpoints/scalemae.pt
  training_metrics: result/training/metrics.json
  inference_dir: result/output
  evaluation_dir: result/evaluation