hugging faces NLP For Sequence Classification with TensorFlow transformers BERT Electra comparison
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Transformers have proven themselves as crucial in many Deep Learning tasks such as text classification in an NLP problem. Here we will use a dataset from Hugging Faces dataset library and train For Sequences classification versions of the Roberta, Electra, XLNet, Deberta, RoFormer, and BERT transformer models. We will compare how each of these models did by comparing the accuracy of train and test predictions. We'll also be comparing training times. We look at retraining only the classification output layer and then training the entire model including the transformer to see the final results.
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