config.yml

allow_cache: true
batch_size: 32
end_ratio_value: 0.0
eval_interval_steps: 500
format: npy
gradient_accumulation_steps: 1
hop_size: 256
is_shuffle: true
log_interval_steps: 200
mel_length_threshold: 32
model_type: tacotron2
num_save_intermediate_results: 1
optimizer_params:
  decay_steps: 150000
  end_learning_rate: 1.0e-05
  initial_learning_rate: 0.001
  warmup_proportion: 0.02
  weight_decay: 0.001
remove_short_samples: true
save_interval_steps: 2000
schedule_decay_steps: 50000
start_ratio_value: 0.5
start_schedule_teacher_forcing: 200001
tacotron2_params:
  attention_dim: 128
  attention_filters: 32
  attention_kernel: 31
  attention_type: lsa
  dataset: kss
  decoder_lstm_units: 1024
  embedding_dropout_prob: 0.1
  embedding_hidden_size: 512
  encoder_conv_activation: relu
  encoder_conv_dropout_rate: 0.5
  encoder_conv_filters: 512
  encoder_conv_kernel_sizes: 5
  encoder_lstm_units: 256
  initializer_range: 0.02
  n_conv_encoder: 5
  n_conv_postnet: 5
  n_lstm_decoder: 1
  n_mels: 80
  n_prenet_layers: 2
  n_speakers: 1
  postnet_conv_filters: 512
  postnet_conv_kernel_sizes: 5
  postnet_dropout_rate: 0.1
  prenet_activation: relu
  prenet_dropout_rate: 0.5
  prenet_units: 256
  reduction_factor: 1
train_max_steps: 200000
use_fixed_shapes: true
var_train_expr: null