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Merge pull request #89 from GrzegorzKarchNV/readme-epochs

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changed number of epochs in train scripts; removed number of epochs f…
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PyTorch/SpeechSynthesis/Tacotron2/README.md
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@ -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 Results section. For both models, the loss values are stored in the
`./output/nvlog.json` log file. `./output/nvlog.json` log file.
After you have trained the Tacotron 2 model for 1500 epochs and the After you have trained the Tacotron 2 and WaveGlow models, you should get audio results similar to the
WaveGlow model for 800 epochs, you should get audio results similar to the
samples in the `./audio` folder. For details about generating audio, see the samples in the `./audio` folder. For details about generating audio, see the
[Inference process](#inference-process) section below. [Inference process](#inference-process) section below.

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PyTorch/SpeechSynthesis/Tacotron2/scripts/train_tacotron2.sh
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@ -1,2 +1,2 @@
mkdir -p output 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

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PyTorch/SpeechSynthesis/Tacotron2/scripts/train_waveglow.sh
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@ -1,2 +1,2 @@
mkdir -p output 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