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Variance floored #8
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How does the synthetic speech sound after training for a few thousand updates? Variance flooring is not an error and training is expected to continue. The corresponding hyperparameter Very low σ-values can indicate a degenerate model that's overfitting to a single observation, and variance flooring is a protection against this. Such flooring is of importance in, for instance, classic decision-tree-based text-to-speech. If you are using the default value |
One way to think about it is that, for high values of |
When I train (in my language - czech), variance floored is sometimes displayed. But train usually continues. Is it a mistake? And how do I fix this error? (my batch size is only 1 - gtx1080 8GB, so it can't be reduced anymore). Could you not describe in HPARAMS what each line means (at least the most important code lines) ?
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