You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi, I recently conducted a few-shot fine-tuning on my private ECG classification training dataset and was surprised by the performance on the test dataset. This high performance occurred after just two epochs, regardless of whether I used an SSL pretrained model or not. My question is: does the model utilize the pretrained weights in both scenarios? Also, are some of the weights frozen during fine-tuning, contributing to the rapid fine-tuning?
The text was updated successfully, but these errors were encountered:
Hi, I recently conducted a few-shot fine-tuning on my private ECG classification training dataset and was surprised by the performance on the test dataset. This high performance occurred after just two epochs, regardless of whether I used an SSL pretrained model or not. My question is: does the model utilize the pretrained weights in both scenarios? Also, are some of the weights frozen during fine-tuning, contributing to the rapid fine-tuning?
The text was updated successfully, but these errors were encountered: