Acurracy = 0 using tensorflow on tabular data
Accuracy is for classification problems (and usually not the best metric anyway). Now, with integer outputs you could treat this as a multiclass classification problem, but you'd need to encode things properly for tensorflow to understand. I'd guess (without really knowing your data, mind) that you'd be better off with regression (so no cross-entropy either).

You also can't use a sigmoid activation on the last layer; it's forcing output predictions between 0 and 1. If you go for regression, you won't need to adjust you true labels, you can use MSE as your metric, and you can just put a linear activator on the last layer.