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Copy pathbase.yml.j2
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100 lines (94 loc) · 2.5 KB
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model_config:
class_name: tensorflow_asr.models.ctc.deepspeech2>DeepSpeech2
config:
name: deepspeech2
speech_config:
sample_rate: 16000
frame_ms: 25
stride_ms: 10
nfft: 512
num_feature_bins: 160
feature_type: spectrogram
augmentation_config:
feature_augment:
time_masking:
prob: 1.0
num_masks: 5
mask_factor: -1 # whole utterance
p_upperbound: 0.05
mask_value: 0
freq_masking:
prob: 1.0
num_masks: 1
mask_factor: 27
mask_value: 0
conv_type: conv2d
conv_kernels: [ [ 11, 41 ], [ 11, 21 ] ]
conv_strides: [ [ 2, 2 ], [ 1, 2 ] ]
conv_filters: [ 32, 32 ]
conv_activation: relu
conv_padding: same
conv_initializer: he_uniform
rnn_nlayers: 5
rnn_type: lstm
rnn_units: 512
rnn_bidirectional: True
rnn_unroll: False
rnn_rowconv: 0
rnn_rowconv_activation: relu
rnn_dropout: 0.5
fc_nlayers: 1
fc_units: 1024
fc_activation: relu
fc_dropout: 0.5
fc_initializer: he_uniform
blank: 0
vocab_size: {{decoder_config.vocabsize}}
kernel_regularizer:
class_name: l2
config:
l2: 0.0005
bias_regularizer:
class_name: l2
config:
l2: 0.0005
learning_config:
optimizer_config:
class_name: Adam
config:
learning_rate:
class_name: ExponentialDecay
module: keras.src.optimizers.schedules.learning_rate_schedule
config:
initial_learning_rate: 0.0001
decay_steps: 5000
decay_rate: 0.9
staircase: True
gwn_config: null
gradn_config: null
batch_size: 16
ga_steps: 4
num_epochs: 450
callbacks:
- class_name: tensorflow_asr.callbacks>TerminateOnNaN
config: {}
- class_name: tensorflow_asr.callbacks>ModelCheckpoint
config:
filepath: {{modeldir}}/checkpoints/{epoch:02d}.weights.h5
save_best_only: False
save_weights_only: True
save_freq: epoch
- class_name: tensorflow_asr.callbacks>TensorBoard
config:
log_dir: {{modeldir}}/tensorboard
histogram_freq: 0
write_graph: False
write_images: False
write_steps_per_second: False
update_freq: batch
profile_batch: 0
- class_name: tensorflow_asr.callbacks>KaggleModelBackupAndRestore
config:
model_handle: {{kaggle_model_handle}}
model_dir: {{modeldir}}
save_freq: epoch