Is this a data issue, or a model issue? A Keras binary classification model
Possible problems: 


You have classes 0 and 0.1. You want to make them 0 and 1 since the formula for the loss function 
$$-{(y\log(p) + (1 - y)\log(1 - p))}$$
expects $y$ to be 0 or 1.
shuffle = False why would you want to turn shuffling off? 
The classes are unbalanced. You have ~100 examples of class 1  and ~20000 total examples. So if you just predict class of everything to be 0 you will be right (20000-100)/20000 = 99.5% times. You can try these tricks and see if they help.