Depending on your problem, some other loss function might work better.
Now to your specific question: Your label values are 0 and 1.
Although the first and last predictions are right, they are only mildly right, while the second prediction is strongly wrong, making the predictions overall more wrong than right.
Your model has a single floating-point output.