Fangjun Kuang 5b6699a835
Minor fixes to the RNN-T Conformer model (#152)
* Disable weight decay.

* Remove input feature batchnorm..

* Replace BatchNorm in the Conformer model with LayerNorm.

* Use tanh in the joint network.

* Remove sos ID.

* Reduce the number of decoder layers from 4 to 2.

* Minor fixes.

* Fix typos.
2021-12-23 13:54:25 +08:00
..

Introduction

The encoder consists of Conformer layers in this folder. You can use the following command to start the training:

cd egs/librispeech/ASR

export CUDA_VISIBLE_DEVICES="0,1,2,3"

./transducer/train.py \
  --world-size 4 \
  --num-epochs 30 \
  --start-epoch 0 \
  --exp-dir transducer/exp \
  --full-libri 1 \
  --max-duration 250 \
  --lr-factor 2.5