From fe3652147a646ede6ef63e31dc80cd4081de8974 Mon Sep 17 00:00:00 2001 From: Michael Hansen Date: Thu, 22 Jun 2023 11:17:49 -0500 Subject: [PATCH] Add note for high quality training --- TRAINING.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/TRAINING.md b/TRAINING.md index 14e12ea..4872d93 100644 --- a/TRAINING.md +++ b/TRAINING.md @@ -170,6 +170,8 @@ python3 -m piper_train \ --precision 32 ``` +Use `--quality high` to train a [larger voice model](https://github.com/rhasspy/piper/blob/master/src/python/piper_train/vits/config.py#L45) (sounds better, but is much slower). + You can adjust the validation split (5% = 0.05) and number of test examples for your specific dataset. For fine-tuning, they are often set to 0 because the target dataset is very small. Batch size can be tricky to get right. It depends on the size of your GPU's vRAM, the model's quality/size, and the length of the longest sentence in your dataset. The `--max-phoneme-ids ` argument to `piper_train` will drop sentences that have more than `N` phoneme ids. In practice, using `--batch-size 32` and `--max-phoneme-ids 400` will work for 24 GB of vRAM (RTX 3090/4090).