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Oceanboi OP t1_ixkfcoh wrote

Reply to comment by asdfzzz2 in [D] Transfer Learning of Image Trained Network in Audio Domain by Oceanboi

So all we really know is that if a model has been trained on some previous task, there’s some arbitrary probability that it can be used for another problem, regardless of image contents or problem domain?

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Think_Olive_1000 t1_ixmm3a2 wrote

Yes, but how well it works will be limited by whether you can find exploit a similarity between the tasks.

Tangentially related: when openai were training their speech recognition model 'whisper' they found that when they trained the model to perform translation it also inexplicably increased the models performance in plain english transcription.

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