I used DenseNet to classify images into some categories.

  
      
      pytorch.org
  
  
    

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As you know, model.train() is called while training a model, and model.eval() is called while evaluating a model.
Before a test by using “evaluation data”,  I used “training data” to evaluate the model,
If the mode is train(), the AAC was 96.25%, but the mode is changed to eval(),  the AAC was 83.02%.
(Of course, the same model and the same training data)
Is there anyone who faces the same problem?
What is the course of the above problem?