Does the validation accuracy remain constant during the training process of a CNN network?

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No, the validation accuracy does not remain constant during the training process of a Convolutional Neural Network (CNN). The validation accuracy typically fluctuates as the network parameters are updated during the training process. In the initial stages of training, the validation accuracy may increase rapidly but may eventually plateau or even decrease if there is overfitting or if the model is not able to learn the important features from the data. Hence, it is important to monitor the validation accuracy during the training process and tune the hyperparameters accordingly to achieve the desired performance.