Questions tagged [loss]

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Why is my validation loss never INcreasing?

I am currently training different neural networks for the binary classification of images. When using the logistic regression, my validation loss never increases, even not after 5000 epochs. I thought ...
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Loss stuck for regression model

I'm training a model that returns 2 parameters. These two parameters are used for classical image processing: a threshold for the kirsch-operator the number of iterations for billateral filter. The ...
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High loss but low rmse, how?

I have trained an lstm model on a dataset but its loss during training is ten times than the rmse during test. How is it possible, and can I use this model if rmse is very low but loss is high? How ...
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Should the model be defined again before training it to new data?

I wanted to fit the LSTM model on new data set in a loop so I have implemented it like this ...
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130 views

Custom loss function for regression

I am trying to write a custom loss function for a machine learning regression task. What I want to accomplish is following: Reward higher preds, higher targets Punish higher preds, lower targets ...
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Logarithmic scale for a learning curve [closed]

I'm plotting the learning curve with Python with the following code: ...
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Decreasing Learning Rate doesn't improve the results

In theory and what people are doing (e.g. Paper) decreasing the learning rate should help the optimizer to go "deeper into the valley" and thus decrease the loss and increase the metric. ...
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The case of (1,478) dim and parameters of neural network to find out

colleagues, actually I am kind'a new to NN, but hard trying.. I have data: Index: 40073 entries (excluded from training, UID) Columns: 484 entries dtypes: bool(468), float64(2), int64(13), object(1) I ...
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NeMo Conformer-CTC Predicts Same Word Repeatedly When Fine-Tuning

I'm using the NeMo Conformer-CTC small on the LibriSpeech dataset (the clean subset, around 29K inputs, using 90% for training and 10% for testing). I use Pytorch Lightning. When I try to train, the ...
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Training Loss increases, but Validation Loss decreases

I am finetuning a T5 transformer model on a sequence to sequence task. My program outputs the training and validation loss every 500 optimization steps. However, when I first started training the ...
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17 views

why the accuracy result and the loss result of an ANN model is inconsistent?

I trained a model based on an ANN and the accuracy is 94.65% almost every time while the loss result is 12.06%. Now my question is shouldn't the loss of the model be (100-94 = 6%) or near it? Why it ...
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HuggingFace Transformers is giving loss: nan - accuracy: 0.0000e+00

I am a HuggingFace Newbie and I am fine-tuning a BERT model (distilbert-base-cased) using the Transformers library but the training loss is not going down, instead ...
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Is my CNN model overfitting or underfitting?

I would like to be sure of whether the model is overfitting or undercutting. Being new to this, is there any specific point to identify when to stop the training process. Any help in this regard would ...
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Q values loss per episode and mean absolute error

I am new to deep reinforcement learning! I am following this code for my adaptation problem (doing actions) https://github.com/jaromiru/AI-blog/blob/master/CartPole-DQN.py I am wondering how I can ...
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Training loss = 0, training accuracy =1, validation and test around 85%

I have created different CNNs for doing image classification. The dataset is this: https://www.kaggle.com/crowww/a-large-scale-fish-dataset There are 9 classes, and each class contains 1000 images of ...
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How to calculate MAE and threshold in a multivariate time series

I'm trying to understand how to calculate the MAE in my time series and then the thresholds to understand which of my data in the test set are anomalies. I'm following this tutorial, which is based on ...
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How to interpret high loss value from model.evaluate() on test data

I'm collecting some metrics for my model's performance using: ...
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31 views

How to increase accuracy and decrease loss of my model

https://jovian.ai/casella0798/badmodel I created the model above to predict red wine quality. I have 6 classes, from 3 to 8. Dataset is unbalanced, with a lot of classes 5 and 6. My model performs ...
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Interpreting Categorical Crossentropy Loss

I would like to ask for clarification about the loss values outputted during training using Categorical Crossentropy as the loss function. If I have 11 categories, and my loss is (for the sake of the ...
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Why are the Loss and Accuracy metrics not suitable?

I have read in a book where it was described that Loss and Accuracy are only conditionally suitable for a statement strength. Other metrics are used like Precision, Recall, ... . Does anyone know a ...
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Accuracy graph of binary classification by CNN [closed]

Why in binary classification of images with CNN the loss and accuracy graph are so unstable? I mean accuracy of validation test does not increase smoothly, it goes to 80%, then comes to 60%, then ...
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Should Discriminator Loss increase or decrease?

This question is purely based on the theoretical aspect of GANs. So, when training a GAN how should the discriminator loss look like? Should the loss of discriminator increase (as the generator is ...
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-2 votes
1 answer
67 views

Why do people prefer $(target-actual)^2$ over $|(target-actual)|$ [duplicate]

When computing loss functions, people use $(target-actual)^2$. They sqaure it to prevent any negative loss. But we can even use $|(target-actual)|$ to prevent any negative loss. So, why do people ...
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2 answers
65 views

Regression problem with Deep Learning

I'm working on the Housing Price dataset, where the target is to predict the housing price. The price of the house will always be positive and according to me, it's possible that the model can predict ...
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Is it vital to use weighted metrics with weighted loss functions?

When one has an imbalanced machine learning problem, let's say a binary classification problem where class 0 is a majority class and class 1 is a minority class. Here class 1 is the most important ...
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