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Home/News/How I improved my fact-checker from F1 0.655 0.813 โ€” what actually changed

How I improved my fact-checker from F1 0.655 0.813 โ€” what actually changed

I built a multilingual fact-checker using XLM-RoBERTa fine-tuned on the FEVER dataset. The first version hit F1 0.655. Not bad, but it kept misfiring on obvious real-world claims. Earth being the third planet from the Sun returned FALSE at 76% confidence. Something was fundamentally wrong. FEVER (Fa

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Tags:#cloud-computing#fact-checking#xlm-roberta#nlp#machine-learning

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