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defaults: |
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- base |
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- _self_ |
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project: text2semantic_finetune_dual_ar |
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max_length: 4096 |
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pretrained_ckpt_path: checkpoints/fish-speech-1.4 |
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trainer: |
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accumulate_grad_batches: 1 |
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gradient_clip_val: 1.0 |
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gradient_clip_algorithm: "norm" |
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max_steps: 1000 |
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precision: bf16-true |
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limit_val_batches: 10 |
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val_check_interval: 100 |
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tokenizer: |
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_target_: transformers.AutoTokenizer.from_pretrained |
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pretrained_model_name_or_path: ${pretrained_ckpt_path} |
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train_dataset: |
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_target_: fish_speech.datasets.semantic.AutoTextSemanticInstructionDataset |
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proto_files: |
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- data/protos |
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tokenizer: ${tokenizer} |
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causal: true |
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max_length: ${max_length} |
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use_speaker: false |
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interactive_prob: 0.7 |
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val_dataset: |
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_target_: fish_speech.datasets.semantic.AutoTextSemanticInstructionDataset |
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proto_files: |
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- data/protos |
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tokenizer: ${tokenizer} |
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causal: true |
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max_length: ${max_length} |
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use_speaker: false |
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interactive_prob: 0.7 |
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data: |
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_target_: fish_speech.datasets.semantic.SemanticDataModule |
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train_dataset: ${train_dataset} |
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val_dataset: ${val_dataset} |
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num_workers: 4 |
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batch_size: 8 |
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tokenizer: ${tokenizer} |
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max_length: ${max_length} |
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model: |
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_target_: fish_speech.models.text2semantic.lit_module.TextToSemantic |
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model: |
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_target_: fish_speech.models.text2semantic.llama.BaseTransformer.from_pretrained |
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path: ${pretrained_ckpt_path} |
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load_weights: true |
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max_length: ${max_length} |
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lora_config: null |
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optimizer: |
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_target_: torch.optim.AdamW |
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_partial_: true |
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lr: 1e-4 |
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weight_decay: 0 |
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betas: [0.9, 0.95] |
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eps: 1e-5 |
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lr_scheduler: |
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_target_: torch.optim.lr_scheduler.LambdaLR |
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_partial_: true |
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lr_lambda: |
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_target_: fish_speech.scheduler.get_constant_schedule_with_warmup_lr_lambda |
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_partial_: true |
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num_warmup_steps: 10 |
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callbacks: |
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model_checkpoint: |
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every_n_train_steps: ${trainer.val_check_interval} |
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