DNABERT
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Sampling of Training Dataset via WeightedRandomSampler for Imbalanced Classes
Hello, I wanted to ask if it is possible to use weighted random sampling for cases of imbalanced datasets? I tried replacing the sampling methods but the tensor dataset for training_dataset is not matching correctly and gives the error: "IndexError: too many indices for tensor of dimension 2."
I think I am missing something in the script. Would appreciate if you could help.
Thank you!