Evaluate CNN model for multiclass image classification
i want to ask what metric can be used to evalutate my CNN model for multi class, i have 3 classes for now and i’m just using accuracy and confussion matrix also plot the loss of model, is there any metric can be used to evaluate my model performance?

Evaluating the performance of a model is one of the most crucial phase of any Machine Learning project cycle and must be done effectively. Since, you have mentioned that you are using accuracy and confusion metrics for the evaluation. I would like to add some points for developing a better evaluation strategy:

Consider you are developing a classifier that classifies an EMAIL into SPAM or NON - SPAM (HAM), now one of the possible evaluation criteria can be the FALSE POSITIVE RATE because it can be really annoying if a non-spam email ends in spam category (which means you will read a valuable email)

So, I recommend you to consider metrics based on the problem you are targeting. There are many metrics such as F1 score, recall, precision that you can choose based on the problem you are havning.

You can visit: https://medium.com/apprentice-journal/evaluating-multi-class-classifiers-12b2946e755b for better understanding. 
