I came across this paper by some Facebook researchers where they found that using a softmax and CE loss function during training led to improved results over si
please I'm trying to build an NLP classifier on top of BERT but I'm struggling with data imbalance. I'm looking for an implementation of weighted CategoricalCro
I am using XGBoost in order to do a sales forecasting. I need a custom objective function, as the value of the prediction depends on the sales price of an item.
I am building a multi-class Vision Transformer Network. When passing my values through my loss function, it always returns zero. My output layer consisits of 37
I'm trying to use a modified version of this custom loss and I'm getting the error below InvalidArgumentError: The second input must be a scalar, but it has sh
I want to implement Pytorch Faster-RCNN module on a custom dataset that I curated and labelled. The implementation detail looks straightforward, there was a dem
I am dealing with a CNN and I get the following error on the line loss = criterion(outputs, data_y): Here is the relevant code snippet: def run(model, X_train,
I try to pass 2 loss functions to a model as Keras allows that. loss: String (name of objective function) or objective function or Loss instance. See losses. I
Is there a way to get the loss of the model, with it's current weights, without running evaluate, or fit, on it? model = keras.Sequential([ keras.layers.In
I want to predict the center of the pupil from an image. so I used a CNN with 3 Dence layer. so the input is an image and the output is a coordinate (X,Y). my m
I am relatively new to PyTorch and Huggingface-transformers and experimented with DistillBertForSequenceClassification on this Kaggle-Dataset. from transformers