You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
94 lines
2.6 KiB
94 lines
2.6 KiB
############################################
|
|
# Network Architecture #
|
|
############################################
|
|
cmvn_file:
|
|
cmvn_file_type: "json"
|
|
# encoder related
|
|
encoder: squeezeformer
|
|
encoder_conf:
|
|
encoder_dim: 256 # dimension of attention
|
|
output_size: 256 # dimension of output
|
|
attention_heads: 4
|
|
num_blocks: 12 # the number of encoder blocks
|
|
reduce_idx: 5
|
|
recover_idx: 11
|
|
feed_forward_expansion_factor: 8
|
|
input_dropout_rate: 0.1
|
|
feed_forward_dropout_rate: 0.1
|
|
attention_dropout_rate: 0.1
|
|
adaptive_scale: true
|
|
cnn_module_kernel: 31
|
|
normalize_before: false
|
|
activation_type: 'swish'
|
|
pos_enc_layer_type: 'rel_pos'
|
|
time_reduction_layer_type: 'conv1d'
|
|
|
|
# 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
|
|
|
|
# hybrid CTC/attention
|
|
model_conf:
|
|
ctc_weight: 0.3
|
|
lsm_weight: 0.1 # label smoothing option
|
|
length_normalized_loss: false
|
|
init_type: 'kaiming_uniform' # !Warning: need to convergence
|
|
|
|
###########################################
|
|
# Data #
|
|
###########################################
|
|
train_manifest: data/manifest.train
|
|
dev_manifest: data/manifest.dev
|
|
test_manifest: data/manifest.test
|
|
|
|
###########################################
|
|
# Dataloader #
|
|
###########################################
|
|
vocab_filepath: data/lang_char/vocab.txt
|
|
spm_model_prefix: ''
|
|
unit_type: 'char'
|
|
preprocess_config: conf/preprocess.yaml
|
|
feat_dim: 80
|
|
stride_ms: 10.0
|
|
window_ms: 25.0
|
|
sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
|
|
batch_size: 32
|
|
maxlen_in: 512 # if input length > maxlen-in, batchsize is automatically reduced
|
|
maxlen_out: 150 # if output length > maxlen-out, batchsize is automatically reduced
|
|
minibatches: 0 # for debug
|
|
batch_count: auto
|
|
batch_bins: 0
|
|
batch_frames_in: 0
|
|
batch_frames_out: 0
|
|
batch_frames_inout: 0
|
|
num_workers: 2
|
|
subsampling_factor: 1
|
|
num_encs: 1
|
|
|
|
###########################################
|
|
# Training #
|
|
###########################################
|
|
n_epoch: 150
|
|
accum_grad: 8
|
|
global_grad_clip: 5.0
|
|
dist_sampler: False
|
|
optim: adam
|
|
optim_conf:
|
|
lr: 0.002
|
|
weight_decay: 1.0e-6
|
|
scheduler: warmuplr
|
|
scheduler_conf:
|
|
warmup_steps: 25000
|
|
lr_decay: 1.0
|
|
log_interval: 100
|
|
checkpoint:
|
|
kbest_n: 50
|
|
latest_n: 5
|