Keras binary classification model is not learning anything. How to improve my model?
I wrote few notes on your implementation:


Classification on imbalanced data can be a problem. How imbalanced is your dataset? You can try to compensate by training your model by feeding balanced mini batches of data. You artificially build each batch so that classes are more or less equally represented, so that your classifier can learn from all of them.
I would change the last layers. I suggest you to use softmax activation at the output layer, and a crossentropy loss function that is specific for this task. The number of output nodes must be equal to the number of classes.
Adam optimizer is commonly referred to as the best algorithm for gradient descent.
MAE is a metric for regression tasks, it doesn't work for classification. You can use 'accuracy' instead.