fake news detection using distilbert trained on liar dataset
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Fakenewsdetection is a text analysis tool designed to identify and classify news articles as either Real or Fake. It leverages advanced AI technology, specifically DistilBERT, which has been trained on the Liar dataset to provide accurate classifications. This tool is particularly useful in today's information age, where misinformation and disinformation are prevalent.
What is DistilBERT?
DistilBERT is a smaller and faster version of the BERT model, known for its high performance in natural language processing tasks while requiring fewer computational resources.
How accurate is Fakenewsdetection?
Fakenewsdetection achieves high accuracy due to its training on the Liar dataset, which contains a large collection of labeled fake and real news articles. However, accuracy may vary depending on the complexity and context of the input text.
Can I use Fakenewsdetection for other languages?
Currently, Fakenewsdetection is optimized for English text. Support for other languages may be added in future updates.