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PaddleSpeech/examples/wenetspeech/asr1/conf/conformer.yaml

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############################################
# Network Architecture #
############################################
cmvn_file_type: "json"
# encoder related
encoder: conformer
encoder_conf:
output_size: 512 # dimension of attention
attention_heads: 8
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
use_cnn_module: True
cnn_module_kernel: 15
cnn_module_norm: layer_norm
activation_type: swish
pos_enc_layer_type: rel_pos
selfattention_layer_type: rel_selfattn
# decoder related
decoder: transformer
decoder_conf:
attention_heads: 8
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
# https://yaml.org/type/float.html
###########################################
# Data #
###########################################
train_manifest: data/train_l/data.list
dev_manifest: data/dev/data.list
test_manifest: data/test_meeting/data.list
###########################################
# Dataloader #
###########################################
use_stream_data: True
unit_type: 'char'
vocab_filepath: data/lang_char/vocab.txt
preprocess_config: conf/preprocess.yaml
cmvn_file: data/mean_std.json
spm_model_prefix: ''
feat_dim: 80
stride_ms: 10.0
window_ms: 25.0
dither: 0.1
sortagrad: 0 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs
batch_size: 32
minlen_in: 10
maxlen_in: 1200 # if input length(number of frames) > maxlen-in, data is automatically removed
minlen_out: 0
maxlen_out: 150 # if output length(number of tokens) > maxlen-out, data is automatically removed
resample_rate: 16000
shuffle_size: 1500 # read number of 'shuffle_size' data as a chunk, shuffle the data in the chunk
sort_size: 1000 # read number of 'sort_size' data as a chunk, sort the data in the chunk
num_workers: 8
prefetch_factor: 10
dist_sampler: True
num_encs: 1
###########################################
# Training #
###########################################
n_epoch: 32
accum_grad: 32
global_grad_clip: 5.0
log_interval: 100
checkpoint:
kbest_n: 50
latest_n: 5
optim: adam
optim_conf:
lr: 0.001
weight_decay: 1.0e-6
scheduler: warmuplr
scheduler_conf:
warmup_steps: 5000
lr_decay: 1.0