how can i get the text tag

[herbiel]

reviews = [
'Reply to win £100 weekly! Where will the 2006 FIFA World Cup be held? Send STOP to 87239 to end service',
'You are awarded a SiPix Digital Camera! call 09061221061 from landline. Delivery within 28days. T Cs Box177. M221BP. 2yr warranty. 150ppm. 16 . p p£3.99',
'it to 80488. Your 500 free text messages are valid until 31 December 2005.',
'Hey Sam, Are you coming for a cricket game tomorrow',
"Why don't you wait 'til at least wednesday to see if you get your ."
]
model.predict(reviews)
array([[0.6472808 ],
[0.7122627 ],
[0.5710311 ],
[0.06721176],
[0.02479185]], dtype=float32)

can i know what's tag on reviews ?

[bilal-24]

if model prediction > 0.5 -> 1:

other situation -> 0:

1 or 0 should equal to spam or ham.

Let's some coding...

[herbiel]

can we make multi-label ,such as 0,1,2,3....

[bilal-24]

Ham -> 0
Spam -> 1

That is the binary classification problem.
Can you show multi label in this problem?

But in another project, we can use sparse_categorical_crossentropy or categorical_crossentropy and then get multi label predictions.

I think you should watch CodeBasic's CNN videos.
He was telling there, you should learn loss functions and label processing.