|
paths: |
|
run_dir: results/${project} |
|
ckpt_dir: ${paths.run_dir}/checkpoints |
|
trainer: |
|
_target_: lightning.pytorch.trainer.Trainer |
|
default_root_dir: ${paths.run_dir} |
|
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: ${paths.ckpt_dir} |
|
filename: step_{step:09d} |
|
save_last: false |
|
save_top_k: 5 |
|
monitor: step |
|
mode: max |
|
every_n_epochs: null |
|
every_n_train_steps: ${trainer.val_check_interval} |
|
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 |
|
logger: |
|
tensorboard: |
|
_target_: lightning.pytorch.loggers.tensorboard.TensorBoardLogger |
|
save_dir: ${paths.run_dir}/tensorboard/ |
|
name: null |
|
log_graph: false |
|
default_hp_metric: true |
|
prefix: '' |
|
train: true |
|
test: false |
|
project: mix_v2 |
|
max_length: 1024 |
|
pretrained_ckpt_path: checkpoints/fish-speech-1.2 |
|
tokenizer: |
|
_target_: transformers.AutoTokenizer.from_pretrained |
|
pretrained_model_name_or_path: ${pretrained_ckpt_path} |
|
train_dataset: |
|
_target_: fish_speech.datasets.semantic.AutoTextSemanticInstructionDataset |
|
proto_files: |
|
- data/protos |
|
tokenizer: ${tokenizer} |
|
causal: true |
|
max_length: ${max_length} |
|
use_speaker: false |
|
interactive_prob: 0.7 |
|
val_dataset: |
|
_target_: fish_speech.datasets.semantic.AutoTextSemanticInstructionDataset |
|
proto_files: |
|
- data/protos |
|
tokenizer: ${tokenizer} |
|
causal: true |
|
max_length: ${max_length} |
|
use_speaker: false |
|
interactive_prob: 0.7 |
|
data: |
|
_target_: fish_speech.datasets.semantic.SemanticDataModule |
|
train_dataset: ${train_dataset} |
|
val_dataset: ${val_dataset} |
|
num_workers: 4 |
|
batch_size: 4 |
|
tokenizer: ${tokenizer} |
|
max_length: ${max_length} |
|
model: |
|
_target_: fish_speech.models.text2semantic.lit_module.TextToSemantic |
|
model: |
|
_target_: fish_speech.models.text2semantic.llama.BaseTransformer.from_pretrained |
|
path: ${pretrained_ckpt_path} |
|
load_weights: true |
|
max_length: ${max_length} |
|
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 |
|
|