Understanding Text with Attention Heatmaps

Multi-head attention is a powerful concept that enhances the attention mechanism in natural language processing by allowing the model to focus on different aspects of a sentence simultaneously, creating comprehensive representations that capture different perspectives. The Attention Heatmap provides an intuitive graphical visualization of these attention scores, allowing users to see which words receive the most emphasis across different attention heads. In Masked Language Model (MLM) tasks within BERT, these concepts work together to accurately predict missing words based on surrounding context, revealing how the model understands relationships and meaning in text. This collaboration ensures that BERT excels at understanding language nuances, helping researchers refine training strategies for improved language comprehension.

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