Fine-tuning BERT for text classification

Fine-tuning BERT for text classification

Key points

• A classification head is added on top of a pre-trained BERT model.
• Text is tokenised into input IDs and attention masks before training.
• Fine-tuning trains the whole model for a few epochs with a small learning rate.