Merge pull request #1005 from zh794390558/conf

[asr]refactor libri s2 conf
pull/1014/head
Hui Zhang 3 years ago committed by GitHub
commit d2d60624bd
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@ -1,36 +1,6 @@
# https://yaml.org/type/float.html
data:
train_manifest: data/manifest.train
dev_manifest: data/manifest.dev
test_manifest: data/manifest.test-clean
collator:
vocab_filepath: data/lang_char/train_960_unigram5000_units.txt
unit_type: spm
spm_model_prefix: data/lang_char/train_960_unigram5000
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
batch_size: 30
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
augmentation_config: conf/augmentation.json
num_workers: 0
subsampling_factor: 1
num_encs: 1
# network architecture
model:
cmvn_file:
cmvn_file_type: "json"
# encoder related
encoder: transformer
encoder_conf:
@ -63,6 +33,33 @@ model:
lsm_weight: 0.1 # label smoothing option
length_normalized_loss: false
data:
train_manifest: data/manifest.train
dev_manifest: data/manifest.dev
test_manifest: data/manifest.test-clean
collator:
vocab_filepath: data/lang_char/train_960_unigram5000_units.txt
unit_type: spm
spm_model_prefix: data/lang_char/train_960_unigram5000
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
batch_size: 30
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
augmentation_config: conf/augmentation.json
num_workers: 0
subsampling_factor: 1
num_encs: 1
training:
n_epoch: 120

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