If Y_pred is very far off from Y, the Loss value will be very high. However, if both values are almost similar, the Loss value will be very low. Hence we need to keep a loss function which can penalize a model effectively while it is training on a dataset.
When a neural network is trying to predict a discrete value, we can consider it to be a classification model. This could be a network trying to predict what kind of animal is present in an image, or whether an email is a spam or not.
Questions tagged [loss-function]
1727 questions
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votes
1 answer
Plot the complete to one loss function
When I plot the loss function of my code I get a nice loss plot.
If I want to plot the 1-hist.history['loss'], how can I do it?
Part of my code:
model = Sequential([
Dense(32, activation='relu', input_shape=(2,)),
Dense(32,…
Ram Rahamim
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- 6
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1 answer
Testing and Confidence score of Network trained with nn.CrossEntropyLoss()
I have trained a network with the following structure:
Intent_LSTM(
(attention): Attention()
(embedding): Embedding(34601, 400)
(lstm): LSTM(400, 512, num_layers=2, batch_first=True, dropout=0.5)
(dropout): Dropout(p=0.5, inplace=False)
(fc):…
Bot_Start
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Implementing BCEWithLogitsLoss from pytorch in keras
I have a model that I am trying to train on a dataset which has a class imbalance. The problem is a multilabel classification problem (each sample has 1 or more labels). I also have weights for each class which I have calculated for my dataset. I…
Kevin
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How to use a particular pixel from the image as a loss function keras?
So I have 100x100x3 images and its a classification problem with 3 categories.
So my CNN architecture is as follows:
visible = Input(shape=(100, 100, 3))
conv_1 = Conv2D(filters=32, kernel_size=(3, 3), strides=(1, 1),…
idpd15
- 448
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- 22
0
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1 answer
Understanding choice of loss and activation in deep autoencoder?
I am following this keras tutorial to create an autoencoder using the MNIST dataset. Here is the tutorial: https://blog.keras.io/building-autoencoders-in-keras.html.
However, I am confused with the choice of activation and loss for the simple…
Jane Sully
- 3,137
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- 87
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0 answers
Tensorflow MeanSquaredError doens't work on one number
I am trying calculate the loss of a network with tensorflow mean squared error, but for some reason it doesn't work if the input tensors only have one number. How should do this instead.
Here is some code:
import tensorflow as tf
loss =…
user12069894
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1 answer
Why does loss decrease but accuracy decreases too (Pytorch, LSTM)?
I have built a model with LSTM - Linear modules in Pytorch for a classification problem (10 classes). I am training the model and for each epoch I output the loss and accuracy in the training set. The ouput is as follows:
epoch: 0 start!
Loss:…
user12546101
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2 answers
How do you gather the elements of y_pred that do not correspond to the true label in a Keras/tf2.0 custom loss function?
Below is a simple example in numpy of what I would like to do:
import numpy as np
y_true = np.array([0,0,1])
y_pred = np.array([0.1,0.2,0.7])
yc = (1-y_true).astype('bool')
desired = y_pred[yc]
>>> desired
>>> array([0.1, 0.2])
So the…
Nick Merrill
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How do I calculate the mean squared error in a neural network with more than one output?
So from what I've understood the formula of the MSE is: MSE= 1/n * ∑(t−y)^2, where n is the number of training sets, t is my target output and y my actual output. Let's say I had 2 training sets each with 1 output:
[0;0] t=[0] y=[1]
[1;1] t=[1]…
L2CH
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- 3
0
votes
1 answer
Loss function variational Autoencoder in Tensorflow example
I have a question regarding the loss function in variational autoencoder. I followed the tensorflow example https://www.tensorflow.org/tutorials/generative/cvae to create a LSTM-VAE, for sampling a sinus function.
My encoder-input is a set of…
0
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1 answer
Tensorflow seq2seq Model, loss value is good, but prediction is false
I'm trying to train a Seq2Seq model. It should translate sentences from a source_vocabulary to sentences in a target_vocabulary.
The loss value is 0.28, but the network doesn't predict words from the target-vocabulary. Instead the predictions of the…
0
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1 answer
How to make a custom loss function in Keras properly
i am making a mode that the prediction is a metrix from a conv layer.
my loss function is
def custom_loss(y_true, y_pred):
print("in loss...")
final_loss = float(0)
print(y_pred.shape)
print(y_true.shape)
for i in range(7):
…
Eshaka
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Can we use sigmoid activation function and binary _crossentropy for one hot encoded labels
I am working on image dataset, where i have one hot encoded labels. Shape of label vector is (3500,8). When i try categorical cross entropy and softmax function in output layer my accuracy is very low. But when i use binary cross entropy and sigmoid…
Talha Anwar
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1 answer
How to create my own loss function in Pytorch?
I'd like to create a model that predicts parameters of a circle (coordinates of center, radius).
Input is an array of points (of arc with noise):
def generate_circle(x0, y0, r, start_angle, phi, N, sigma):
theta =…
ashy_fox
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- 2
0
votes
1 answer
How to use haversine function as loss function while training model in Tensorflow?
I want to train a LSTM model to predict the position(latitude,longitude) of the ocean float. I try to use the haversine loss function, but I dont't know how to implement it.
To be exact, I use the Keras and the shape of the model output is…
Vickyyyy
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