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VoxCPM/conf/voxcpm_v1.5/voxcpm_finetune_lora.yaml
2025-12-05 21:04:51 +08:00

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800 B
YAML

pretrained_path: /path/to/VoxCPM1.5/
train_manifest: /path/to/train.jsonl
val_manifest: null
sample_rate: 44100
batch_size: 16
grad_accum_steps: 1 # Gradient accumulation steps, >1 can increase effective batch size without increasing memory
num_workers: 2
num_iters: 2000
log_interval: 10
valid_interval: 1000
save_interval: 1000
learning_rate: 0.0001
weight_decay: 0.01
warmup_steps: 100
max_steps: 2000
max_batch_tokens: 8192 # Example: single batch can have at most 16k tokens, with batch_size=4, each sample can have at most 4096 tokens
save_path: /path/to/checkpoints/finetune_lora
tensorboard: /path/to/logs/finetune_lora
lambdas:
loss/diff: 1.0
loss/stop: 1.0
lora:
enable_lm: true
enable_dit: true
enable_proj: false
r: 32
alpha: 16
dropout: 0.0