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Unreliable News Classifier (English)
Trained, validate, and tested using a subset of the NELA-GT-2018 dataset. The dataset is split such that there was no overlap in of news sources between the three sets.
This model used the pre-trained weights of distilbert-base-cased as starting point (only 4 layers) and was able to achieve 84% accuracy on the test set. It has less than 1% difference in performance compared to the BERT based model while having 2.0x the speed.
For more details: Github
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