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Hi, I looked at BEANS as well, but not clear how to use the model for a classification tasks, and for fine tuning.
Consider the classification of wav files, with multiple classes, of a species, or of a specific specimen.
Can you show how to fine tune and classify?
Example:
Train file | labels file1.wav ['stress', 'mating', 'addressee_1'] file2.wav ['feeding', 'stress', 'addressee_2']
...
Predict test.wav > ['stress', 'feeding' , 'addressee_3'] # number of labels may vary
The text was updated successfully, but these errors were encountered:
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Hi, I looked at BEANS as well, but not clear how to use the model for a classification tasks, and for fine tuning.
Consider the classification of wav files, with multiple classes, of a species, or of a specific specimen.
Can you show how to fine tune and classify?
Example:
Train
file | labels
file1.wav ['stress', 'mating', 'addressee_1']
file2.wav ['feeding', 'stress', 'addressee_2']
...
Predict
test.wav > ['stress', 'feeding' , 'addressee_3'] # number of labels may vary
The text was updated successfully, but these errors were encountered: