# How to understand 'losses' in Spacy's custom NER training engine?

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.

• Just to add to the accepted answer, the specific value of the loss is meaningless, you just want it to go down during training. Jun 24 at 6:09