What does the output of model.predict function from Keras mean? I have built a LSTM model to predict duplicate questions on the Quora official dataset. The test labels are 0 or 1. 1 indicates the question pair is duplicate. After building the model using model.fit, I test the model using model.predict on the test data. The output is an array of values something like below:

 [ 0.00514298]
 [ 0.15161049]
 [ 0.27588326]
 [ 0.00236167]
 [ 1.80067325]
 [ 0.01048524]
 [ 1.43425131]
 [ 1.99202418]
 [ 0.54853892]
 [ 0.02514757]


I am only showing the first 10 values in the array. I don't understand what do these values mean and what is the predicted label for each question pair?
The output of a neural network will never, by default, be binary - i.e. zeros or ones. The network works with continuous values (not discrete) in order to optimise the loss more freely in the framework of gradient descent.

Have a look here at a similar question that also shows some code. 

Without any kind of tweaking and scaling, the output of your network is likely to fall somewhere in the range of your input, in terms of its nominal value. In your case, that seems to be roughly between 0 and 2.

You could now write a function that turns your values above into 0 or 1, based on some threshold. For example, scale the values to be in the range [0, 1], then if the value is below 0.5, return 0, if above 0.5, return 1.