changed number of epochs in train scripts; removed number of epochs from readme for the audio samples

PyTorch/SpeechSynthesis/Tacotron2/README.md

@@ -137,8 +137,7 @@ Ensure your loss values are comparable to those listed in the table in the
 Results section. For both models, the loss values are stored in the 
 `./output/nvlog.json` log file. 
 
-After you have trained the Tacotron 2 model for 1500 epochs and the 
-WaveGlow model for 800 epochs, you should get audio results similar to the 
+After you have trained the Tacotron 2 and WaveGlow models, you should get audio results similar to the
 samples in the `./audio` folder. For details about generating audio, see the 
 [Inference process](#inference-process) section below.
 

PyTorch/SpeechSynthesis/Tacotron2/scripts/train_tacotron2.sh

@@ -1,2 +1,2 @@
 mkdir -p output
-python -m multiproc train.py -m Tacotron2 -o ./output/ -lr 1e-3 --epochs 2001 -bs 80 --weight-decay 1e-6 --grad-clip-thresh 1.0 --cudnn-benchmark=True --log-file ./output/nvlog.json --anneal-steps 500 1000 1500 --anneal-factor 0.1 --fp16-run
+python -m multiproc train.py -m Tacotron2 -o ./output/ -lr 1e-3 --epochs 1500 -bs 80 --weight-decay 1e-6 --grad-clip-thresh 1.0 --cudnn-benchmark=True --log-file ./output/nvlog.json --anneal-steps 500 1000 1500 --anneal-factor 0.1 --fp16-run

PyTorch/SpeechSynthesis/Tacotron2/scripts/train_waveglow.sh

@@ -1,2 +1,2 @@
 mkdir -p output
-python -m multiproc train.py -m WaveGlow -o ./output/ -lr 1e-4 --epochs 2001 -bs 8 --segment-length  8000 --weight-decay 0 --grad-clip-thresh 65504.0 --epochs-per-checkpoint 50 --cudnn-benchmark=True --log-file ./output/nvlog.json --fp16-run
+python -m multiproc train.py -m WaveGlow -o ./output/ -lr 1e-4 --epochs 1000 -bs 8 --segment-length  8000 --weight-decay 0 --grad-clip-thresh 65504.0 --epochs-per-checkpoint 50 --cudnn-benchmark=True --log-file ./output/nvlog.json --fp16-run