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---|---|---|
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# network architecture | ||
# encoder related | ||
encoder: conformer | ||
encoder_conf: | ||
output_size: 512 | ||
attention_heads: 4 | ||
linear_units: 2048 | ||
num_blocks: 12 | ||
dropout_rate: 0.1 | ||
positional_dropout_rate: 0.1 | ||
attention_dropout_rate: 0.1 | ||
input_layer: conv2d | ||
normalize_before: true | ||
macaron_style: true | ||
pos_enc_layer_type: "rel_pos" | ||
selfattention_layer_type: "rel_selfattn" | ||
activation_type: "swish" | ||
use_cnn_module: true | ||
cnn_module_kernel: 31 | ||
# 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: 0.1 | ||
src_attention_dropout_rate: 0.1 | ||
|
||
optim: adam | ||
optim_conf: | ||
lr: 0.0005 | ||
scheduler: warmuplr # pytorch v1.1.0+ required | ||
scheduler_conf: | ||
warmup_steps: 5000 | ||
max_epoch: 200 | ||
batch_size: 64 | ||
|
||
specaug: specaug | ||
specaug_conf: | ||
apply_time_warp: true | ||
time_warp_window: 5 | ||
time_warp_mode: bicubic | ||
apply_freq_mask: true | ||
freq_mask_width_range: | ||
- 0 | ||
- 30 | ||
num_freq_mask: 2 | ||
apply_time_mask: true | ||
time_mask_width_range: | ||
- 0 | ||
- 40 | ||
num_time_mask: 2 | ||
|
||
best_model_criterion: | ||
- - valid | ||
- acc | ||
- max | ||
keep_nbest_models: 10 |
85 changes: 85 additions & 0 deletions
85
egs2/iemocap/asr1/conf/tuning/train_asr_conformer_hubert.yaml
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,85 @@ | ||
# network architecture | ||
# encoder related | ||
encoder: conformer | ||
encoder_conf: | ||
output_size: 512 | ||
attention_heads: 8 | ||
linear_units: 2048 | ||
num_blocks: 12 | ||
dropout_rate: 0.1 | ||
positional_dropout_rate: 0.1 | ||
attention_dropout_rate: 0.1 | ||
input_layer: conv2d | ||
normalize_before: true | ||
macaron_style: true | ||
pos_enc_layer_type: "rel_pos" | ||
selfattention_layer_type: "rel_selfattn" | ||
activation_type: "swish" | ||
use_cnn_module: true | ||
cnn_module_kernel: 31 | ||
|
||
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: 0.1 | ||
src_attention_dropout_rate: 0.1 | ||
|
||
optim: adam | ||
optim_conf: | ||
lr: 0.0002 | ||
scheduler: warmuplr # pytorch v1.1.0+ required | ||
scheduler_conf: | ||
warmup_steps: 25000 | ||
max_epoch: 50 | ||
|
||
freeze_param: [ | ||
"frontend.upstream" | ||
] | ||
|
||
frontend_conf: | ||
n_fft: 512 | ||
hop_length: 256 | ||
|
||
frontend: s3prl | ||
frontend_conf: | ||
frontend_conf: | ||
upstream: hubert_large_ll60k # Note: If the upstream is changed, please change the input_size in the preencoder. | ||
download_dir: ./hub | ||
multilayer_feature: True | ||
|
||
preencoder: linear | ||
preencoder_conf: | ||
input_size: 1024 # Note: If the upstream is changed, please change this value accordingly. | ||
output_size: 80 | ||
|
||
model_conf: | ||
ctc_weight: 0.3 | ||
lsm_weight: 0.1 | ||
length_normalized_loss: false | ||
extract_feats_in_collect_stats: false # Note: "False" means during collect stats (stage 10), generating dummy stats files rather than extract_feats by forward frontend. | ||
|
||
specaug: specaug | ||
specaug_conf: | ||
apply_time_warp: true | ||
time_warp_window: 5 | ||
time_warp_mode: bicubic | ||
apply_freq_mask: true | ||
freq_mask_width_range: | ||
- 0 | ||
- 30 | ||
num_freq_mask: 2 | ||
apply_time_mask: true | ||
time_mask_width_range: | ||
- 0 | ||
- 40 | ||
num_time_mask: 2 | ||
|
||
best_model_criterion: | ||
- - valid | ||
- acc | ||
- max | ||
keep_nbest_models: 10 |
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Original file line number | Diff line number | Diff line change |
---|---|---|
|
@@ -71,7 +71,7 @@ | |
"torch_optimizer", | ||
"fairscale", | ||
"transformers", | ||
"gtn", | ||
"gtn==0.0.0", | ||
], | ||
"setup": [ | ||
"numpy<=1.21.3", | ||
|
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