StreamingVocos_16khz / configs /default.yaml
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# Global Seed # https://lightning.ai/docs/pytorch/stable/common/trainer.html#reproducibility
seed_everything: 3407
# Custom
ignore_warnings: false # Ignore warnings
test_after_fit: false # Apply test after fit finished
git_commit_before_fit: false # Commit before fit
# Trainer Config https://lightning.ai/docs/pytorch/stable/common/trainer.html
trainer:
# Train, Validate, Test and Predict
max_epochs: -1
min_epochs: null
max_steps: -1
min_steps: null
max_time: null
num_sanity_val_steps: 2
check_val_every_n_epoch: 1
val_check_interval: null
overfit_batches: 0.0
limit_train_batches: null
limit_val_batches: null
limit_test_batches: null
limit_predict_batches: null
# Device https://lightning.ai/docs/pytorch/stable/common/trainer.html#accelerator
accelerator: gpu # "cpu", "gpu", "tpu", "ipu", "auto"
devices: "0," # "2," for device id 2
num_nodes: 1 # https://lightning.ai/docs/pytorch/stable/common/trainer.html#num-nodes
# Distributed
strategy: auto # https://lightning.ai/docs/pytorch/stable/common/trainer.html#strategy
sync_batchnorm: false # https://lightning.ai/docs/pytorch/stable/common/trainer.html#sync-batchnorm
use_distributed_sampler: true # https://lightning.ai/docs/pytorch/stable/common/trainer.html#lightning.pytorch.trainer.Trainer.params.use_distributed_sampler
# Logger https://lightning.ai/docs/pytorch/latest/visualize/loggers.html
# https://lightning.ai/docs/pytorch/latest/api_references.html#loggers
logger:
# https://lightning.ai/docs/pytorch/latest/api/lightning.pytorch.loggers.wandb.html#module-lightning.pytorch.loggers.wandb
class_path: WandbLogger
init_args:
save_dir: logs
project: xarts
log_model: false
log_every_n_steps: 50
# Callbacks https://lightning.ai/docs/pytorch/latest/extensions/callbacks.html
callbacks:
# https://lightning.ai/docs/pytorch/latest/api/lightning.pytorch.callbacks.ModelCheckpoint.html#lightning.pytorch.callbacks.ModelCheckpoint
- class_path: ModelCheckpoint
init_args:
filename: epoch={epoch:02d}-val_loss={val/mel/loss:.4f}
monitor: val/mel/loss
verbose: true
save_last: true
save_top_k: 2
mode: min
auto_insert_metric_name: false
# https://lightning.ai/docs/pytorch/latest/api/lightning.pytorch.callbacks.EarlyStopping.html#lightning.pytorch.callbacks.EarlyStopping
# - class_path: EarlyStopping
# init_args:
# monitor: val/acc
# min_delta: 0.01
# patience: 20
# verbose: true
# mode: max
# strict: true
# https://lightning.ai/docs/pytorch/latest/api/lightning.pytorch.callbacks.LearningRateMonitor.html#lightning.pytorch.callbacks.LearningRateMonitor
- class_path: LearningRateMonitor
init_args:
logging_interval: epoch
# Gradient Clipping https://lightning.ai/docs/pytorch/stable/common/trainer.html#gradient-clip-val
gradient_clip_val: null
gradient_clip_algorithm: null
# Gradient Accumulation https://lightning.ai/docs/pytorch/stable/common/trainer.html#accumulate-grad-batches
accumulate_grad_batches: 1
# Precision https://lightning.ai/docs/pytorch/stable/common/trainer.html#precision
precision: 32-true
# Plugins https://lightning.ai/docs/pytorch/stable/common/trainer.html#plugins
plugins: null
# Debug
fast_dev_run: false # https://lightning.ai/docs/pytorch/stable/common/trainer.html#fast-dev-run
profiler: null # https://lightning.ai/docs/pytorch/stable/api_references.html#profiler
barebones: false
detect_anomaly: false
reload_dataloaders_every_n_epochs: 0
# Misc
inference_mode: true
default_root_dir: null
benchmark: null
deterministic: false
enable_progress_bar: true
enable_checkpointing: true
enable_model_summary: true