For questions about the validation loss, i.e. the loss of a model (e.g. a neural network) computed on the validation data (or dataset), which is different from the testing/test data (i.e. the data that you use after having trained your model(s) and selected the best model according to the validation loss/performance).
Questions tagged [validation-loss]
9 questions
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Fluctuations in loss during in epoch evaluation of GRU
I am training a one-layer unidirectional vanilla GRU on a next item prediction task with regard to the last 10 interacted items. In my original experiment, where I trained on approx. 5.5M samples and validated on around 1M samples, I saw periodic…
PatrickSVM
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React on train-validation curve after trening
I have a regression task that I tray to solve with AI.
I have around 6M rows with about 30 columns. (originally there was 100, but I reduce it with drop feature importance)
I understand basic principle: Look if model overfit or underfit - according…
Marko Zadravec
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Final Model Training Problem - Overfitting
I am working on a CNN project for multiclass classification. I implemented hyperparameter optimization to find the most suitable model, during which I got a best accuracy of 97.38%. I then took this model and applied Early Stopping to it, but the…
Zelreedy
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What are possible reasons for the validation loss increasing with more data?
I trained a neural network on an NLP problem and compared the loss and BLEU score on the validation data with the same training parameters in two scenarios: a) when I trained on 25% of the data, b) when I trained on 100% of the data. I observed a…
postnubilaphoebus
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When to stop training object detection network, while taking into the acount 3 factors: loss ,validation loss, mAP
as far as I know, and as can be seen here
enter link description here
it is quite clear that it is better to stop at the "turning point" where the validation loss starts growing.
What I do not understand is two things:
As can be seen here:
my…
Igor
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How to select pseudo label samples that minimize validation loss?
I have a problem about meta pseudo labeling, I want to select the most significant pseudo-labels that minimize validation loss. Let's say i initialize a set of pseudo label denoted $Y_{pseudo}$, then i perform parameter update by gradient…
Việt Nguyễn
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What would be a good cost function based on both saliency-maps and labels?
I have a number of input samples where: every input sample has both a label and a reference-map. This reference-map gives a score to each location of an input sample. The score defines how much this location of the input sample SHOULD contribute to…
Wtt
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What can cause massive instability in validation loss?
I'm working with very weird data that is apparently very hard to fit.
And I've noticed a very strange phenomenon where it can go from roughly 0.0176 validation MSE to 1534863.6250 validation MSE in only 1 epoch! It usually then will return to a very…
profPlum
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Is it okay to calculate the validation loss over batches instead of the whole validation set for speed purposes?
I have about 2000 items in my validation set, would it be reasonable to calculate the loss/error after each epoch on just a subset instead of the whole set, if calculating the whole dataset is very slow?
Would taking random mini-batches to calculate…
Ilknur Mustafa
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