pretrained_path: /path/to/VoxCPM2/
train_manifest: /path/to/train.jsonl
val_manifest: null
sample_rate: 16000        # AudioVAE encoder input rate; must match audio_vae_config.sample_rate
out_sample_rate: 48000    # AudioVAE decoder output rate; only used at inference, not during training
batch_size: 2
grad_accum_steps: 8  # effective batch size = batch_size × grad_accum_steps = 16
num_workers: 8
num_iters: 1000
log_interval: 10
valid_interval: 500
save_interval: 500
learning_rate: 0.0001
weight_decay: 0.01
warmup_steps: 100
max_steps: 1000
max_batch_tokens: 8192
save_path: /path/to/checkpoints/finetune_lora
tensorboard: /path/to/logs/finetune_lora
lambdas:
  loss/diff: 1.0
  loss/stop: 1.0

# LoRA configuration
lora:
  enable_lm: true
  enable_dit: true
  enable_proj: false
  r: 32
  alpha: 32
  dropout: 0.0

# Distribution options (optional)
# - If distribute=false (default): save pretrained_path as base_model in lora_config.json
# - If distribute=true: save hf_model_id as base_model (hf_model_id is required)
# hf_model_id: "openbmb/VoxCPM2"
# distribute: true