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- # network architecture
- # encoder related
- encoder: transformer
- encoder_conf:
- output_size: 256 # dimension of attention
- attention_heads: 4
- linear_units: 2048 # the number of units of position-wise feed forward
- num_blocks: 12 # the number of encoder blocks
- dropout_rate: 0.1
- positional_dropout_rate: 0.1
- attention_dropout_rate: 0.0
- input_layer: conv2d # encoder architecture type
- normalize_before: true
- # decoder related
- decoder: transformer
- decoder_conf:
- attention_heads: 4
- linear_units: 2048
- num_blocks: 6
- dropout_rate: 0.1
- positional_dropout_rate: 0.1
- self_attention_dropout_rate: 0.0
- src_attention_dropout_rate: 0.0
- # frontend related
- frontend: wav_frontend
- frontend_conf:
- fs: 16000
- window: hamming
- n_mels: 80
- frame_length: 25
- frame_shift: 10
- lfr_m: 1
- lfr_n: 1
- # hybrid CTC/attention
- model_conf:
- ctc_weight: 0.3
- lsm_weight: 0.1 # label smoothing option
- length_normalized_loss: false
- # optimization related
- accum_grad: 1
- grad_clip: 5
- patience: none
- max_epoch: 60
- val_scheduler_criterion:
- - valid
- - acc
- best_model_criterion:
- - - valid
- - acc
- - max
- keep_nbest_models: 10
- # NoamLR is deprecated. Use WarmupLR.
- # The following is equivalent setting for NoamLR:
- #
- # optim: adam
- # optim_conf:
- # lr: 10.
- # scheduler: noamlr
- # scheduler_conf:
- # model_size: 256
- # warmup_steps: 25000
- #
- optim: adam
- optim_conf:
- lr: 0.002
- scheduler: warmuplr # pytorch v1.1.0+ required
- scheduler_conf:
- warmup_steps: 25000
- dataset_conf:
- data_names: speech,text
- data_types: sound,text
- shuffle: True
- shuffle_conf:
- shuffle_size: 2048
- sort_size: 500
- batch_conf:
- batch_type: token
- batch_size: 25000
- num_workers: 8
- log_interval: 50
- normalize: None
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