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add e-branchformer result for tedlium3 and add checker for text output length #5130
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1e45a7f
add e-branchformer result for tedlium3 and add checker for text outpu…
Some-random 3473631
add GPU conf for lm training
Some-random 18d5bed
fix merge conflict in README
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[pre-commit.ci] auto fixes from pre-commit.com hooks
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add model link and put e-branchformer result in the front
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Merge branch 'tedlium3' of https://github.com/Some-random/espnet into…
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[pre-commit.ci] auto fixes from pre-commit.com hooks
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Merge branch 'espnet:master' into tedlium3
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tuning/train_asr_conformer.yaml | ||
conf/tuning/train_asr_e_branchformer_size256_mlp1024_e12_mactrue.yaml |
81 changes: 81 additions & 0 deletions
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egs2/tedlium3/asr1/conf/tuning/train_asr_e_branchformer_size256_mlp1024_e12_mactrue.yaml
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# Trained with NVIDIA V100 GPU (32GB) x 4 | ||
encoder: e_branchformer | ||
encoder_conf: | ||
output_size: 256 | ||
attention_heads: 4 | ||
attention_layer_type: rel_selfattn | ||
pos_enc_layer_type: rel_pos | ||
rel_pos_type: latest | ||
cgmlp_linear_units: 1024 | ||
cgmlp_conv_kernel: 31 | ||
use_linear_after_conv: false | ||
gate_activation: identity | ||
num_blocks: 12 | ||
dropout_rate: 0.1 | ||
positional_dropout_rate: 0.1 | ||
attention_dropout_rate: 0.1 | ||
input_layer: conv2d | ||
layer_drop_rate: 0.0 | ||
linear_units: 1024 | ||
positionwise_layer_type: linear | ||
use_ffn: true | ||
macaron_ffn: true | ||
merge_conv_kernel: 31 | ||
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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 | ||
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model_conf: | ||
ctc_weight: 0.3 | ||
lsm_weight: 0.1 | ||
length_normalized_loss: false | ||
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frontend_conf: | ||
n_fft: 512 | ||
win_length: 400 | ||
hop_length: 160 | ||
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seed: 2022 | ||
use_amp: true | ||
num_workers: 6 | ||
batch_type: numel | ||
batch_bins: 50000000 | ||
accum_grad: 1 | ||
max_epoch: 50 | ||
init: none | ||
best_model_criterion: | ||
- - valid | ||
- acc | ||
- max | ||
keep_nbest_models: 10 | ||
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optim: adam | ||
optim_conf: | ||
lr: 0.002 | ||
weight_decay: 0.000001 | ||
scheduler: warmuplr | ||
scheduler_conf: | ||
warmup_steps: 15000 | ||
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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 | ||
- 27 | ||
num_freq_mask: 2 | ||
apply_time_mask: true | ||
time_mask_width_ratio_range: | ||
- 0. | ||
- 0.05 | ||
num_time_mask: 5 |
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Original file line number | Diff line number | Diff line change |
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# Trained with NVIDIA V100 GPU (32GB) x 4 | ||
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lm: transformer | ||
lm_conf: | ||
pos_enc: null | ||
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@sw005320 @Some-random Sorry, really late on that (I didn't sync w/ master in a while) but why was it added and how was the limit defined?
I was a bit confused when I saw that thousand of warnings were displayed in my training logs!
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Yes, it was added to a warning of the large memory consumption, but
100
is probably too small.So, we can change it to
500
or more.Sorry about it.
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Thanks and no worries, I'll open a PR!
Edit: You're too fast for me Professor! 😄