Here, the main objective is to create a system with the BERT model for classifying SMS messages as spam or non-spam to enhance potential security. First, reproduce the results. Then, enhance the 'epochs = 20' in the 'Training the model' and other relevant sections. Now, let us know your observations. Do you see any improvements in the prediction accuracy?
Plot the generated image at 4000 epoch. Let us know your following observations: Can we generate the same quality of the input MNIST image? Will the discriminator be fooled by this image quality? MNIST dataset descriptions: The MNIST database contains 60,000 training images and 10,000 testing images of handwritten digits. The MNIST dataset is present in Keras; you do not have to upload it externally while doing this assignment.
First, reproduce the results for 100 epochs. Then reduce the epoch value to 50. State your following observations:
(i) Do you observe any change in the training results according to their values in latent space vectors in comparison to the results obtained in 100 epochs?
(ii) Do you observe any change in the scatter plot of training data on the basis of their values of corresponding latent dimensions generated from the encoder in comparison to the results obtained in 100 epochs?