Why does my Transformer-based text generation model produce incoherent sequences

Question

Can you tell me why my Transformer-based text generation model produces incoherent sequences?

Answer 1

Incoherent sequences in Transformer-based text generation models can result from issues like improper temperature settings, insufficient training, or a lack of diversity in the training data.

Here is the code snippet showing how:

In the above code, we are using the following:

• Temperature: A high temperature (e.g., temperature=1.0) can cause randomness, while a lower value (e.g., 0.7) reduces randomness and improves coherence.
• Beam Search: Using beam search (num_beams=5) instead of greedy sampling allows the model to explore multiple possible outputs, improving coherence.
• Insufficient Training: Ensure the model has been sufficiently fine-tuned on high-quality, diverse data to avoid incoherent sequences.