srch

14.02.2020 · I’m trying to create my own network to train on the iris dataset. But the loss is not decreasing after 10000 iterations import torch import random import numpy as np import torch.nn as nn from sklearn.datasets import load_breast_cancer,load_iris from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score …

Look at the data as you feed it as well as the labels (matplotlib plots, etc). Perhaps you're misaligning input with output (cropping issues, ...

22.03.2019 · Loss not decreasing - Pytorch. Ask Question Asked 2 years, 9 months ago. Active 2 years, 6 months ago. Viewed 12k times 1 I am using dice loss for my implementation of a Fully Convolutional Network(FCN) which involves hypernetworks. The model has two inputs ...

I am building a network for image classification using the MNIST dataset. I've managed to get the model to train but my loss is not decreasing ...

The only way the NN can learn now is by memorising the training set, which means that the training loss will decrease very slowly, while the test loss will ...

When taken at dim=0, the loss hovers around 2.30x. When taken at dim=1, the loss hovers around 4.15x. 1. Continue this thread. level 1. dhecloud. · 1y. Use Adam optim. If loss decreases, means it’s a hyper parameter problem with SGD. if not, it’s a problem with code or data.

28.04.2019 · lossi=loss(y2,labels) optimizer.zero_grad() lossi.backward() optimizer.step() Hence, the parameters to train are a1,b1,… a6,b6. In the above piece of code, my when I print my loss it does not decrease at all. It always stays the same equal to 2.30 epoch 0 loss = 2.308579206466675 epoch 1 loss = 2.297269344329834 epoch 2 loss = 2.3083386421203613

Loss doesn't decrease in Pytorch CNN · 1. The main issue with this code is that you're using the wrong output shape and the wrong loss function for ...

04.04.2018 · Hi, I am new to deeplearning and pytorch, I write a very simple demo, but the loss can’t decreasing when training. Any comments are highly appreciated! I want to use one hot to represent group and resource, there are 2 group and 4 resouces in training data: group1 (1, 0) can access resource 1(1, 0, 0, 0) and resource2(0, 1, 0, 0) group2(0, 1) can access resource3(0, 0, 1, …

Apart from the comment I made, I reduced the dropout and learning rate as well. Model seems to train now but the train loss is increasing and decreasing ...

13.06.2019 · I tried training the model on a small data sample of 10 samples. The initial loss was 20.636. The loss stagnated at 19.803 after around 7500 epochs. The loss decreased very slowly but continuously through these epochs. So, I guess it is not overfitting at all. Please let me know if I can clarify anything else about the code.

02.04.2021 · I have defined a custom loss function but the loss function is not decreasing, not even changing. my loss function aims to minimize the inverse of gap statistic which is used to evaluate the cluster formed from my embeddings. this is a toy code: def get_data(): Xlist = [] for i in range(6): X, _ = make_blobs(n_samples=1000, n_features=2) Xlist.append(X) dat = …

BCELoss in PyTorch (not a Lightning issue). I was able to get consistent results be removing the final sigmoid operation, and using nn.

Hi, I am new to deeplearning and pytorch, I write a very simple demo, but the loss can't decreasing when training.