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Update README.md
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README.md
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@@ -200,8 +200,11 @@ The dataset that is generated contains 8000 train examples, 1000 validation exam
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- target.wav = the dry audio file
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- wet_effects.pt = serialized PyTorch file that contains a list of the effects applied to the wet audio file
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Note: if training, this process will be done automatically at the start of training. To disable this, set `render_files=False` in the config or command-line, and set `render_root={path/to/dataset}` if it is in a custom location.
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## Experimental parameters
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Some relevant dataset/training parameters descriptions
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- `num_kept_effects={[min, max]}` range of <b> Kept </b> effects to apply to each file. Inclusive.
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- target.wav = the dry audio file
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- wet_effects.pt = serialized PyTorch file that contains a list of the effects applied to the wet audio file
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The effects list is in the order of Reverb, Chorus, Delay, Distortion, Compressor
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Note: if training, this process will be done automatically at the start of training. To disable this, set `render_files=False` in the config or command-line, and set `render_root={path/to/dataset}` if it is in a custom location.
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## Experimental parameters
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Some relevant dataset/training parameters descriptions
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- `num_kept_effects={[min, max]}` range of <b> Kept </b> effects to apply to each file. Inclusive.
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