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XTTS v1.1 GPT Trainer #3086

Merged
merged 24 commits into from
Oct 25, 2023
Merged

XTTS v1.1 GPT Trainer #3086

merged 24 commits into from
Oct 25, 2023

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Edresson
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@Edresson Edresson commented Oct 19, 2023

XTTS GPT Trainer for XTTS v1.1.

ToDos:

  • Update Docs
  • Update recipe with the released checkpoints
  • Rebase the PR to update the code with the changes done in XTTS v1.1 release.

@CLAassistant
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CLAassistant commented Oct 19, 2023

CLA assistant check
All committers have signed the CLA.

@Edresson Edresson requested review from WeberJulian and erogol and removed request for WeberJulian October 23, 2023 13:44
@erogol
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erogol commented Oct 24, 2023

Looks good to me. Waiting for @WeberJulian

Yuzuuu69

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@coqui-ai coqui-ai deleted a comment from Yuzuuu69 Oct 25, 2023
@WeberJulian
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I'm not 100% sure that we should use those values BATCH_SIZE 3 and GRAD_ACUMM_STEPS 84 for fine-tuning. In some extreme cases (small datasets) a single step will be more than an epoch. Why not use the values we use internally 8 and 1 ?

@WeberJulian
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Otherwise, it looks good to me too. Great work. In future PRs, we can focus on reducing the VRAM footprint of fine-tuning to something more reasonable that you can do on collab with 16Gb of VRAM.

@erogol erogol merged commit 16ba377 into dev Oct 25, 2023
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@erogol erogol deleted the xtts_trainer branch October 25, 2023 11:28
@markrmiller
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That's interesting that you use 8/1 internally. The comments say you need an effective batch size of like 230 or something for good quality. Regardless, it would seem difficult to use a small dataset, in my limited experience, the model overfits pretty quickly, even with a much reduced learning rate, even with a decent sized data set. I'm still trying to get anywhere near a good voice match before it overfits.

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6 participants