32kHz Vocos Multi Speaker Model Training Log about vocos HOT 10 OPEN

@LEECHOONGHO I have published my model here https://huggingface.co/patriotyk/vocos-mel-hifigan-compat-44100khz
Sounds great, and there is metrics.
@Mahmoud-ghareeb My model has been trained on 800+ hours of audio. Vocoder doesn't require text transcripts so you can easily use audio books for training. You even don't need to cut it by silence because vocos anyway internally splits provided audios to smaller segments.

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Do you have a standard tensorboard logs? It is interesting to compare.

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@patriotyk Sorry, I've change the code to log on WandB server. I have no local logging files nor tensorboard logs.

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What is your validation loss on the last checkpoint? It is encoded in to the checkpoint file name. I am training 44100 for an almost a week already and loss still goes down.

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Training Loss, Generated Outputs.

I hope this will be a reference for model training.

https://api.wandb.ai/links/xi-speech-team/k0kdfwch

TKS for your work,could your share 32k model training detail like:
your encodec model(i found pretrained models :24k and 48k,so i guess 32k resample to 24k or 48k for encodec pretrained model,then resample to 32k ??)

from vocos.

Training Loss, Generated Outputs.
I hope this will be a reference for model training.
https://api.wandb.ai/links/xi-speech-team/k0kdfwch

TKS for your work,could your share 32k model training detail like: your encodec model(i found pretrained models :24k and 48k,so i guess 32k resample to 24k or 48k for encodec pretrained model,then resample to 32k ??)

I'm sry for your confuse.
I just trained Mel Vocoder not for encodec's decoder.

But I have plans to train Mel-Encodec?(Mel Spectrogram to RVQ Encoder, and Vocos Decoder for Various Speech data) in the future.

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Do you have a standard tensorboard logs? It is interesting to compare.

What is your validation loss on the last checkpoint? It is encoded in to the checkpoint file name. I am training 44100 for an almost a week already and loss still goes down.

I estimated mel loss, and Generator loss with newly gained dataset. and each was 0.0942 and 2.82.
Because of the dataset's Size, estimating Eval loss with eval dataset have no difference with sampled train data.

how about your model output's quality? any artifacts?

from vocos.

Do you have a standard tensorboard logs? It is interesting to compare.

What is your validation loss on the last checkpoint? It is encoded in to the checkpoint file name. I am training 44100 for an almost a week already and loss still goes down.

I estimated mel loss, and Generator loss with newly gained dataset. and each was 0.0942 and 2.82. Because of the dataset's Size, estimating Eval loss with eval dataset have no difference with sampled train data.

how about your model output's quality? any artifacts?

I am still training(third week). It is very slow. I will update with my results when finish.

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how much data do we need for training

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Great work! @patriotyk, Thank you so much

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