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NVIDIA Deep Learning Examples
Jasper checkpoint (PyTorch, AMP, LibriSpeech)
Model
NVIDIA Deep Learning Examples
Jasper checkpoint (PyTorch, AMP, LibriSpeech)

Jasper PyTorch checkpoint trained on LibriSpeech (test-other 9.66% WER)

2 Versions
20.10.0
02/10/2021 12:37 AM UTC1.24 GBAccuracy: 0440 EpochsBatch Size: 512GPU: A100
architecture
KeyValue
typejasper10x5dr_speedp-online_speca: SpecAugment (2x20, 3x75); Speed perturbation U(0.85, 1.15)
performance
KeyValue
dev_clean_wer3.20
dev_other_wer9.74
test_clean_wer3.38
test_other_wer9.66
training
KeyValue
batch_size512
datasetLibriSpeech
epochs440
training_precisionAMP
19.08.0Selected
08/21/2020 1:36 AM UTC2.48 GBAccuracy: 0400 EpochsBatch Size: 0GPU: V100
architecture
KeyValue
dense_residual_connnectionsTrue
layers50 conv layers - 10 blocks - each 5 subblocks
model_configsjasper10x5dr_sp_offline_specaugment.toml
performance
KeyValue
WER (on Librispeech dev-clean)<3.64%
training
KeyValue
bs512
cudnnbenchmark
epochs400
gpuV100
gpus8
grad_acc_steps1
lr0.015
lr_decayquadratic
optimnovograd
spec_augTrue
speed_perturb1.0;0.9;1.1
wd1e-3
1-2 of 2 items

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