What is ‘from_logits=True’ in Keras/TensorFlow Loss Functions?

Deep learning frameworks like Keras lower the barrier to entry for the masses and democratize the development of DL models to unexperienced folk, who can rely on reasonable defaults and simplified APIs to bear the brunt of heavy lifting, and produce decent results. A common confusion arises between newer deep learning practitioners when using Keras … Read more

deep learning – Bert model does not work after loss change

My model finetunes bert (specifically Roberta) using a lst fully connected layer of a binary text classification task. I was using cross entropy loss and the code worked well. However when I changed the loss the model stopped learning and predicted 0 for all the examples and did not learn. For other classification tasks the … Read more

python – Training a deep learning network for MRI reconstruction but loss and SSIM values ​​go to NaN after a few iterations

I’m currently working on a project to train a deep learning network to denoise MRI reconstructions in Pytorch but I’m running into issues in the training process where my loss and SSIM becomes NaN after a few iterations. From what I’ve gathered so far, it’s an issue with the gradients becoming too large and thus … Read more

keras – Non-activate custom loss function/metrics in Tensorflow 2.x

I am trying to learn TensorFlow from its guide available on its website. I am having issues debugging the following lines of code where I compute the custom loss function. I am using the following model: low = 0 high = 100 xtrain = [[i,i*2] for i in range(low,high)] xtrain_ab = [[i,i*3] for i in … Read more

python – How can I determine validation loss for faster RCNN (PyTorch)?

Thank you so much for your patience. I’ve posted below a snippet of code that iterates over the dataloader. I think I’ve understood you but from what I’ve done below I get an empty dictionary when I print out the losses: @torch.no_grad() def evaluate_loss(model, data_loader, device): val_loss = 0 for images, targets in data_loader: images … Read more