| model: | |
| _target_: fish_speech.models.text2semantic.lit_module.TextToSemantic | |
| model: | |
| _target_: fish_speech.models.text2semantic.llama.BaseTransformer.from_pretrained | |
| path: checkpoints/fish-speech-1.2 | |
| load_weights: true | |
| max_length: 1024 | |
| lora_config: | |
| _target_: fish_speech.models.text2semantic.lora.LoraConfig | |
| r: 8 | |
| lora_alpha: 16 | |
| lora_dropout: 0.01 | |
| optimizer: | |
| _target_: torch.optim.AdamW | |
| _partial_: true | |
| lr: 0.0001 | |
| weight_decay: 0.01 | |
| betas: | |
| - 0.9 | |
| - 0.95 | |
| eps: 1.0e-05 | |
| lr_scheduler: | |
| _target_: torch.optim.lr_scheduler.LambdaLR | |
| _partial_: true | |
| lr_lambda: | |
| _target_: fish_speech.scheduler.get_constant_schedule_with_warmup_lr_lambda | |
| _partial_: true | |
| num_warmup_steps: 50 | |
| model/params/total: 495286272 | |
| model/params/trainable: 5017600 | |
| model/params/non_trainable: 490268672 | |
| data: | |
| _target_: fish_speech.datasets.semantic.SemanticDataModule | |
| train_dataset: | |
| _target_: fish_speech.datasets.semantic.AutoTextSemanticInstructionDataset | |
| proto_files: | |
| - data/protos | |
| tokenizer: | |
| _target_: transformers.AutoTokenizer.from_pretrained | |
| pretrained_model_name_or_path: checkpoints/fish-speech-1.2 | |
| causal: true | |
| max_length: 1024 | |
| use_speaker: false | |
| interactive_prob: 0.7 | |
| val_dataset: | |
| _target_: fish_speech.datasets.semantic.AutoTextSemanticInstructionDataset | |
| proto_files: | |
| - data/protos | |
| tokenizer: | |
| _target_: transformers.AutoTokenizer.from_pretrained | |
| pretrained_model_name_or_path: checkpoints/fish-speech-1.2 | |
| causal: true | |
| max_length: 1024 | |
| use_speaker: false | |
| interactive_prob: 0.7 | |
| num_workers: 4 | |
| batch_size: 4 | |
| tokenizer: | |
| _target_: transformers.AutoTokenizer.from_pretrained | |
| pretrained_model_name_or_path: checkpoints/fish-speech-1.2 | |
| max_length: 1024 | |
| trainer: | |
| _target_: lightning.pytorch.trainer.Trainer | |
| default_root_dir: results/mix_v2 | |
| accelerator: gpu | |
| num_nodes: 1 | |
| devices: auto | |
| strategy: | |
| _target_: lightning.pytorch.strategies.DDPStrategy | |
| process_group_backend: nccl | |
| precision: bf16-true | |
| check_val_every_n_epoch: null | |
| val_check_interval: 1000 | |
| max_steps: 100000 | |
| benchmark: true | |
| accumulate_grad_batches: 1 | |
| gradient_clip_val: 1.0 | |
| gradient_clip_algorithm: norm | |
| limit_val_batches: 10 | |
| callbacks: | |
| model_checkpoint: | |
| _target_: lightning.pytorch.callbacks.ModelCheckpoint | |
| dirpath: results/mix_v2/checkpoints | |
| filename: step_{step:09d} | |
| save_last: false | |
| save_top_k: 5 | |
| monitor: step | |
| mode: max | |
| every_n_epochs: null | |
| every_n_train_steps: 1000 | |
| auto_insert_metric_name: false | |
| model_summary: | |
| _target_: lightning.pytorch.callbacks.ModelSummary | |
| max_depth: 2 | |
| learning_rate_monitor: | |
| _target_: lightning.pytorch.callbacks.LearningRateMonitor | |
| logging_interval: step | |
| log_momentum: false | |
| grad_norm_monitor: | |
| _target_: fish_speech.callbacks.GradNormMonitor | |
| norm_type: 2 | |
| logging_interval: step | |
| extras: null | |
| task_name: null | |
| tags: null | |
| ckpt_path: null | |
| seed: null | |