custom training data split
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Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 20/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- machine-learning
Research direction
Start by reading binarize.py and the data/raw layout, then trace how the specified Opencpop segment file is selected for training. Done means establishing whether a partial dataset can be used as described and providing a reproducible workflow or clearly identifying the missing support.
Written by the indexing model from the issue text.
Description
hello. Thanks for sharing your great research!
I'm going to do an experiment to see the effect of data size on diffsinger model training.
So, I want to train using only a part of the opencpop data, but I am having a hard time figuring out how to use only the specified segment file for training.
Can I just make the desired data exist in data/raw and then run binarize.py?
It would be a great help if you could give me an answer.
thank you!
- Dominant language
- Python
- Stars
- 4.9k
- Forks
- 826
- PR merge metrics
- No merged PRs in 30d
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