mirror of
https://github.com/OpenBMB/VoxCPM
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36 lines
1.1 KiB
YAML
36 lines
1.1 KiB
YAML
pretrained_path: /path/to/VoxCPM-0.5B/
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train_manifest: /path/to/train.jsonl
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val_manifest: null
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sample_rate: 16000
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batch_size: 16
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grad_accum_steps: 1 # Gradient accumulation steps, >1 can increase effective batch size without increasing memory
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num_workers: 2
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num_iters: 2000
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log_interval: 10
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valid_interval: 1000
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save_interval: 1000
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learning_rate: 0.0001
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weight_decay: 0.01
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warmup_steps: 100
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max_steps: 2000
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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
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save_path: /path/to/checkpoints/finetune_lora
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tensorboard: /path/to/logs/finetune_lora
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lambdas:
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loss/diff: 1.0
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loss/stop: 1.0
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# LoRA configuration
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lora:
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enable_lm: true
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enable_dit: true
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enable_proj: false
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r: 32
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alpha: 16
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dropout: 0.0
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# Distribution options (optional)
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# - If distribute=false (default): save pretrained_path as base_model in lora_config.json
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# - If distribute=true: save hf_model_id as base_model (hf_model_id is required)
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# hf_model_id: "openbmb/VoxCPM-0.5B"
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# distribute: true |