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.
90 lines
2.5 KiB
90 lines
2.5 KiB
3 years ago
|
# https://yaml.org/type/float.html
|
||
|
|
###########################################
|
||
|
|
# Data #
|
||
|
|
###########################################
|
||
|
|
train_manifest: data/manifest.es.train
|
||
|
|
dev_manifest: data/manifest.es.dev
|
||
|
|
test_manifest: data/manifest.es.test
|
||
|
|
|
||
|
|
###########################################
|
||
|
|
# Dataloader #
|
||
|
|
###########################################
|
||
|
|
vocab_filepath: data/lang_1spm/train_sp.en-es.es_bpe8000_units_tc.txt
|
||
|
|
unit_type: 'spm'
|
||
|
|
spm_model_prefix: data/lang_1spm/train_sp.en-es.es_bpe8000_tc
|
||
|
|
mean_std_filepath: ""
|
||
|
|
# preprocess_config: conf/augmentation.json
|
||
|
|
batch_size: 20
|
||
|
|
feat_dim: 83
|
||
|
|
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
|
||
|
|
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
|
||
|
|
preprocess_config:
|
||
|
|
num_workers: 0
|
||
|
|
subsampling_factor: 1
|
||
|
|
num_encs: 1
|
||
|
|
|
||
|
|
|
||
|
|
############################################
|
||
|
|
# Network Architecture #
|
||
|
|
############################################
|
||
|
|
cmvn_file: None
|
||
|
|
cmvn_file_type: "json"
|
||
|
|
# 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 input type, you can chose conv2d, conv2d6 and conv2d8
|
||
|
|
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
|
||
|
|
|
||
|
|
# hybrid CTC/attention
|
||
|
|
model_conf:
|
||
|
|
asr_weight: 0.0
|
||
|
|
ctc_weight: 0.0
|
||
|
|
lsm_weight: 0.1 # label smoothing option
|
||
|
|
length_normalized_loss: false
|
||
|
|
|
||
|
|
|
||
|
|
###########################################
|
||
|
|
# Training #
|
||
|
|
###########################################
|
||
|
|
n_epoch: 40
|
||
|
|
accum_grad: 2
|
||
|
|
global_grad_clip: 5.0
|
||
|
|
optim: adam
|
||
|
|
optim_conf:
|
||
|
|
lr: 2.5
|
||
|
|
weight_decay: 0.
|
||
|
|
scheduler: noam
|
||
|
|
scheduler_conf:
|
||
|
|
warmup_steps: 25000
|
||
|
|
lr_decay: 1.0
|
||
|
|
log_interval: 50
|
||
|
|
checkpoint:
|
||
|
|
kbest_n: 50
|
||
|
|
latest_n: 5
|