Comments (2)
datumbox
commented on July 22, 2024
There is most likely something wrong with the way the model is trained because the model size sounds huge for the given data input. In which language are your texts written? If that language does not separate characters by space, your "vocabulary" will end up being huge sentences. Unfortunately without additional info I can't suggest something better.
I advise you to load the model on your IDE and debug/profile it. Check out what type of features it learned by inspecting the loaded objects, the size of the vocabularies etc. Datumbox is capable of parsing thousands of sentences per second, so the 40+ sec per tweet sounds weird.
Hope it helps!
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dilipbobby
commented on July 22, 2024
I trained model with raw twitter English tweets only.I will check once again by following your suggestions 👍 thank you :)
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