# Model architecture
model:
  input_dim: 3  # RGB images
  hidden_dim: 512
  num_blocks: 8
  num_heads: 8
  patch_size: 8
  patch_stride: 4
  time_freq_dim: 256
  time_max_period: 1024
  mlp_ratio: 4
  use_bias: false
  padding: "SAME"
  pos_embed_cls_token: false
  pos_embed_extra_tokens: 0

# Training parameters
training:
  learning_rate: 1.0e-4
  batch_size: 128
  num_steps: 1_000_000
  warmup_pct: 0.01
  weight_decay: 0.0
  grad_clip_norm: 100.0
  
# Checkpointing and logging
checkpointing:
  log_every: 1_000
  plot_every: 10_000
  save_every: 10_000
  resume_from_checkpoint: null

# Data
data:
  train_split: 0.9  # 90% for training, 10% for testing
  random_seed: 42