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1 vote
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Is it methodologically correct to use the data to be used for finetuning in the pretrain phase of the BERT model?

I'd say that it's correct. BERT pre-training doesn't use labels, as it uses two self-supervised objectives: masked language model (mask a word in the middle of a sentence, and guess what it is) next ...
Valentin Calomme's user avatar
2 votes

What specific problems in what domains and fields have the need to use rule-based text classification?

Pretty much all of them. I can't see a field that couldn't benefit from some rule-based approach. The thing here is that we often talk about ML Models when, typically, they are ML Systems. What's the ...
Valentin Calomme's user avatar
2 votes

Improve text classification accuracy

I've recently finished a similar project using this open-sourced model which is based on the DeBERTaV3-base. https://huggingface.co/knowledgator/comprehend_it-base It performs well in the zero-shot ...
mikepetterson's user avatar
2 votes

Improve text classification accuracy

You can try using simple transformer architecture, you can find reference for tuning it on hugging face. I think it will be able to get more context from the data you described. Here is a useful link:...
priyanshu chaudhary's user avatar

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