matcha-ljspeech / config.yaml
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copies to try matxa-hf
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task_name: train
run_name: ljspeech
tags:
- ljspeech
train: true
test: true
ckpt_path: null
seed: 1234
data:
_target_: matcha.data.text_mel_datamodule.TextMelDataModule
name: ljspeech
train_filelist_path: data/LJSpeech-1.1/train.txt
valid_filelist_path: data/LJSpeech-1.1/val.txt
batch_size: 32
num_workers: 20
pin_memory: true
cleaners:
- english_cleaners2
add_blank: true
n_spks: 1
n_fft: 1024
n_feats: 80
sample_rate: 22050
hop_length: 256
win_length: 1024
f_min: 0
f_max: 8000
data_statistics:
mel_mean: -5.536622
mel_std: 2.116101
seed: ${seed}
load_durations: false
model:
_target_: matcha.models.matcha_tts.MatchaTTS
n_vocab: 178
n_spks: ${data.n_spks}
spk_emb_dim: 64
n_feats: 80
data_statistics: ${data.data_statistics}
out_size: null
prior_loss: true
use_precomputed_durations: ${data.load_durations}
encoder:
encoder_type: RoPE Encoder
encoder_params:
n_feats: ${model.n_feats}
n_channels: 192
filter_channels: 768
filter_channels_dp: 256
n_heads: 2
n_layers: 6
kernel_size: 3
p_dropout: 0.1
spk_emb_dim: 64
n_spks: 1
prenet: true
duration_predictor_params:
filter_channels_dp: ${model.encoder.encoder_params.filter_channels_dp}
kernel_size: 3
p_dropout: ${model.encoder.encoder_params.p_dropout}
decoder:
channels:
- 256
- 256
dropout: 0.05
attention_head_dim: 64
n_blocks: 1
num_mid_blocks: 2
num_heads: 2
act_fn: snakebeta
cfm:
name: CFM
solver: euler
sigma_min: 0.0001
optimizer:
_target_: torch.optim.Adam
_partial_: true
lr: 0.0001
weight_decay: 0.0
callbacks:
model_checkpoint:
_target_: lightning.pytorch.callbacks.ModelCheckpoint
dirpath: ${paths.output_dir}/checkpoints
filename: checkpoint_{epoch:03d}
monitor: epoch
verbose: false
save_last: true
save_top_k: 10
mode: max
auto_insert_metric_name: true
save_weights_only: false
every_n_train_steps: null
train_time_interval: null
every_n_epochs: 100
save_on_train_epoch_end: null
model_summary:
_target_: lightning.pytorch.callbacks.RichModelSummary
max_depth: 3
rich_progress_bar:
_target_: lightning.pytorch.callbacks.RichProgressBar
logger:
tensorboard:
_target_: lightning.pytorch.loggers.tensorboard.TensorBoardLogger
save_dir: ${paths.output_dir}/tensorboard/
name: null
log_graph: false
default_hp_metric: true
prefix: ''
trainer:
_target_: lightning.pytorch.trainer.Trainer
default_root_dir: ${paths.output_dir}
max_epochs: -1
accelerator: gpu
devices:
- 0
precision: 16-mixed
check_val_every_n_epoch: 1
deterministic: false
gradient_clip_val: 5.0
paths:
root_dir: ${oc.env:PROJECT_ROOT}
data_dir: ${paths.root_dir}/data/
log_dir: ${paths.root_dir}/logs/
output_dir: ${hydra:runtime.output_dir}
work_dir: ${hydra:runtime.cwd}
extras:
ignore_warnings: false
enforce_tags: true
print_config: true