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
I would like to ask you a question, I pre-train on my medical image data set (6k) according to the official pre-training code, and then the downstream task is segmentation, but the fine-tuning results with my own pre-training model is always inferior to the author's pre-training model with imagenet, which is why, is my pre-training data is still too small?
The text was updated successfully, but these errors were encountered:
Hey,
Your dataset seems too small compared to Imagenet-1K. A suggestion - you should initialize your model using the pre-trained model weights of Imagenet and then continue pre-training on your medical image dataset, which you can use for your downstream task. Please let me know how this goes for you.
Hey, Your dataset seems too small compared to Imagenet-1K. A suggestion - you should initialize your model using the pre-trained model weights of Imagenet and then continue pre-training on your medical image dataset, which you can use for your downstream task. Please let me know how this goes for you.
Ok, thank you very much for your reply. Next, I will try according to what you said. Thanks again
I would like to ask you a question, I pre-train on my medical image data set (6k) according to the official pre-training code, and then the downstream task is segmentation, but the fine-tuning results with my own pre-training model is always inferior to the author's pre-training model with imagenet, which is why, is my pre-training data is still too small?
The text was updated successfully, but these errors were encountered: