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downstream_expert:
datarc:
batch_size: 32
bucket_file: /app/data/LibriSpeech/len_for_bucket
decoder_args:
beam: 5
beam_threshold: 25
criterion: ctc
decoder_type: None
kenlm_model: /path/to/KenLM
lexicon: /path/to/4-gram.arpa
lm_weight: 2
nbest: 1
sil_weight: 0
unk_weight: -math.inf
word_score: -1
dev-clean:
- dev-clean
dev-other:
- dev-other
dict_path: ./downstream/asr/char.dict
eval_batch_size: 1
libri_root: /app/data/LibriSpeech
num_workers: 12
test-clean:
- test-clean
test-other:
- test-other
train:
- train-clean-100
train_batch_size: 32
zero_infinity: true
modelrc:
RNNs:
bidirection: true
dim:
- 1024
- 1024
dropout:
- 0.2
- 0.2
layer_norm:
- false
- false
module: LSTM
proj:
- false
- false
sample_rate:
- 1
- 1
sample_style: concat
total_rate: -1
Wav2Letter:
total_rate: 320
project_dim: 1024
select: RNNs
optimizer:
lr: 0.0001
name: TorchOptim
torch_optim_name: Adam
runner:
eval_dataloaders:
- dev-clean
eval_step: 2000
gradient_accumulate_steps: 1
gradient_clipping: 1
log_step: 100
max_keep: 1
save_step: 5
total_steps: 10
specaug:
apply_freq_mask: true
apply_time_mask: true
apply_time_warp: true
freq_mask_width_range:
- 0
- 50
num_freq_mask: 4
num_time_mask: 2
time_mask_width_range:
- 0
- 40
time_warp_window: 5
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