I can relate, I was also confused at first 
The output of the model will indeed not be a probability distribution, it’s simply a linear function of the layer before (which is also linear in this case).
The softmax will transform this linear output into a probability distribution: more reading below.

  
      en.wikipedia.org
  
  
    

Softmax function 3

In mathematics, the softmax function takes an un-normalized vector, and normalizes it into a probability distribution. That is, prior to applying softmax, some vector elements could be negative, or greater than one; and might not sum to 1; but after applying softmax, each element 
  
    
      
        
          x
          
            i
          
        
      
    
    {\displaystyle x_{i}}
  
 is in the interval 
  
    
      
        [
        0
        ,
        1
        ]
      
    ...