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More info on pretrained models #1
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Hey Fabian! hope you're well :)!
Note, that we did not try do any optimization on these scores and did not use any MUSDB training data in the training process so these scores are an actual measure of the generalization power of the model (on western pop/rock song though). There are some more detailed on the extended abstract of the demo we'll present in ISMIR next week. |
@romi1502 thanks for the info. I think, especially for the research community, it would be cool to also present reproducible scores when just trained on MUSDB18. By doing it yourself, you might prevent people from using non-ideal parameters, hence, reporting scores that are too low. Oh and also we can save a bit of energy for the environment ;-) |
Hi @faroit Thanks for your Feedback. Training on musdb is definitely something we can do but I'm not sure how much value it would bring to end users. |
Could you please share how large was your dataset for the pretrained models? |
@mmoussallam I understand that but at one point people will use this to train on their own data and might publish results based on this repo. I already trained and evaluated on MUSDB18 and it seems that there are some issues - See #81 |
@mmoussallam I am closing this issue since it is not related to the pretrained beans model. Feel free to reply here or in #81 |
First, congrats to your release. Glad to have more music separation ready to use :-)
Do you have some more information regarding
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