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From the tid-bits, I understand of neural networks (NN), the Loss function is the difference between predicted output and expected output of the NN. I am following this tutorial, the losses are included at line #81 in the nlp.update() function.

I am getting losses in the range 300-100. How to interpret them? What should be the ideal output of this losses variable? I went through Spacy's documentation, but nothing much is written there about losses. Also, please let me know the links to relevant theories to understand this in general.

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  • $\begingroup$ Just to add to the accepted answer, the specific value of the loss is meaningless, you just want it to go down during training. $\endgroup$
    – polm23
    Jun 24 at 6:09
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A critical goal of training a neural network is to minimize the loss. Loss is not explained for spaCy because it is a general concept for machine learning and deep learning. Loss is not specific to spaCy and although there are some finer details I don't believe that is your inquiry.

In general, to understand loss functions, I recommend the following resources:

If you like videos watch:

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