Your language model fails to recognize idiomatic expressions during fine-tuning How can these be captured effectively

Question

With the help of code can you explain to me if Your language model fails to recognize idiomatic expressions during fine-tuning. How can these be captured effectively?

Answer 1

Capture idiomatic expressions effectively by augmenting training data with diverse idiomatic samples, using contrastive learning, and incorporating phrase-aware embeddings.

Here is the code snippet you can refer to:

In the above code we are using the following key approaches:

• Idiom-Enriched Data Augmentation:
  • Expands training data with diverse idiomatic expressions and their contextual meanings.
• Contrastive Learning:
  • Uses a contrastive loss function to differentiate idiomatic vs. literal meanings.
• Phrase-Aware Embeddings:
  • Enhances token representations to recognize multi-word idioms.
• Contextualized Pretraining:
  • Fine-tunes BERT or GPT models on idiom-heavy corpora to improve comprehension.

Hence, by applying contrastive learning, idiom-specific data augmentation, and phrase-aware embeddings, the language model effectively captures idiomatic expressions, improving contextual understanding during fine-tuning.