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Why my model shows metrics like this? While my model was training recall and precision was equal to zero? I trying to do binary classification of mushrooms [edible, poisonous]. I have CNN model with some dropout and batch normalization. Dataset have ~7000 img, ration is equal to both class.
Python version is 3.10 Tensorflow version is 2.12
It seems like your model is not generalizing properly. During training its performance on the traning set increases as it should but it fails to capture general properties in your data that would make it able to predict data in your validation dataset. It also seems to somewhat classify everything in your validation dataset into either of the classes, eg "everything is edible".
This can have various reasons, the most obvious are that your model is not suited for this task or that you don't have enough data. See Wikipedia for a more in-depth explanation:
https://en.wikipedia.org/wiki/Overfitting
