matcha-ljspeech / config_tree.log
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CONFIG
β”œβ”€β”€ data
β”‚ └── _target_: matcha.data.text_mel_datamodule.TextMelDataModule
β”‚ name: ljspeech
β”‚ train_filelist_path: data/LJSpeech-1.1/train.txt
β”‚ valid_filelist_path: data/LJSpeech-1.1/val.txt
β”‚ batch_size: 32
β”‚ num_workers: 20
β”‚ pin_memory: true
β”‚ cleaners:
β”‚ - english_cleaners2
β”‚ add_blank: true
β”‚ n_spks: 1
β”‚ n_fft: 1024
β”‚ n_feats: 80
β”‚ sample_rate: 22050
β”‚ hop_length: 256
β”‚ win_length: 1024
β”‚ f_min: 0
β”‚ f_max: 8000
β”‚ data_statistics:
β”‚ mel_mean: -5.536622
β”‚ mel_std: 2.116101
β”‚ seed: 1234
β”‚ load_durations: false
β”‚
β”œβ”€β”€ model
β”‚ └── _target_: matcha.models.matcha_tts.MatchaTTS
β”‚ n_vocab: 178
β”‚ n_spks: 1
β”‚ spk_emb_dim: 64
β”‚ n_feats: 80
β”‚ data_statistics:
β”‚ mel_mean: -5.536622
β”‚ mel_std: 2.116101
β”‚ out_size: null
β”‚ prior_loss: true
β”‚ use_precomputed_durations: false
β”‚ encoder:
β”‚ encoder_type: RoPE Encoder
β”‚ encoder_params:
β”‚ n_feats: 80
β”‚ n_channels: 192
β”‚ filter_channels: 768
β”‚ filter_channels_dp: 256
β”‚ n_heads: 2
β”‚ n_layers: 6
β”‚ kernel_size: 3
β”‚ p_dropout: 0.1
β”‚ spk_emb_dim: 64
β”‚ n_spks: 1
β”‚ prenet: true
β”‚ duration_predictor_params:
β”‚ filter_channels_dp: 256
β”‚ kernel_size: 3
β”‚ p_dropout: 0.1
β”‚ decoder:
β”‚ channels:
β”‚ - 256
β”‚ - 256
β”‚ dropout: 0.05
β”‚ attention_head_dim: 64
β”‚ n_blocks: 1
β”‚ num_mid_blocks: 2
β”‚ num_heads: 2
β”‚ act_fn: snakebeta
β”‚ cfm:
β”‚ name: CFM
β”‚ solver: euler
β”‚ sigma_min: 0.0001
β”‚ optimizer:
β”‚ _target_: torch.optim.Adam
β”‚ _partial_: true
β”‚ lr: 0.0001
β”‚ weight_decay: 0.0
β”‚
β”œβ”€β”€ callbacks
β”‚ └── model_checkpoint:
β”‚ _target_: lightning.pytorch.callbacks.ModelCheckpoint
β”‚ dirpath: /workspace/Matcha-TTS/logs/train/ljspeech/runs/2024-10-19_19-
β”‚ filename: checkpoint_{epoch:03d}
β”‚ monitor: epoch
β”‚ verbose: false
β”‚ save_last: true
β”‚ save_top_k: 10
β”‚ mode: max
β”‚ auto_insert_metric_name: true
β”‚ save_weights_only: false
β”‚ every_n_train_steps: null
β”‚ train_time_interval: null
β”‚ every_n_epochs: 100
β”‚ save_on_train_epoch_end: null
β”‚ model_summary:
β”‚ _target_: lightning.pytorch.callbacks.RichModelSummary
β”‚ max_depth: 3
β”‚ rich_progress_bar:
β”‚ _target_: lightning.pytorch.callbacks.RichProgressBar
β”‚
β”œβ”€β”€ logger
β”‚ └── tensorboard:
β”‚ _target_: lightning.pytorch.loggers.tensorboard.TensorBoardLogger
β”‚ save_dir: /workspace/Matcha-TTS/logs/train/ljspeech/runs/2024-10-19_19
β”‚ name: null
β”‚ log_graph: false
β”‚ default_hp_metric: true
β”‚ prefix: ''
β”‚
β”œβ”€β”€ trainer
β”‚ └── _target_: lightning.pytorch.trainer.Trainer
β”‚ default_root_dir: /workspace/Matcha-TTS/logs/train/ljspeech/runs/2024-10
β”‚ max_epochs: -1
β”‚ accelerator: gpu
β”‚ devices:
β”‚ - 0
β”‚ precision: 16-mixed
β”‚ check_val_every_n_epoch: 1
β”‚ deterministic: false
β”‚ gradient_clip_val: 5.0
β”‚
β”œβ”€β”€ paths
β”‚ └── root_dir: /workspace/Matcha-TTS
β”‚ data_dir: /workspace/Matcha-TTS/data/
β”‚ log_dir: /workspace/Matcha-TTS/logs/
β”‚ output_dir: /workspace/Matcha-TTS/logs/train/ljspeech/runs/2024-10-19_19
β”‚ work_dir: /workspace/Matcha-TTS
β”‚
β”œβ”€β”€ extras
β”‚ └── ignore_warnings: false
β”‚ enforce_tags: true
β”‚ print_config: true
β”‚
β”œβ”€β”€ task_name
β”‚ └── train
β”œβ”€β”€ run_name
β”‚ └── ljspeech
β”œβ”€β”€ tags
β”‚ └── ['ljspeech']
β”œβ”€β”€ train
β”‚ └── True
β”œβ”€β”€ test
β”‚ └── True
β”œβ”€β”€ ckpt_path
β”‚ └── None
└── seed
└── 1234