Part 7/9:
Augmentation and Fine-Tuning Enhancement
Further advanced techniques include:
Using the OpenAI Edit API to augment existing data, making responses more detailed or coherent.
Increasing diversity by editing longer outputs for additional richness.
Adjusting generation parameters like temperature to balance randomness and coherency.
He hints that these steps—especially data augmentation—can improve model robustness beyond initial data synthesis.
Practical Tips and Troubleshooting
Throughout the tutorial, Shapiro shares valuable insights:
Monitoring outputs actively during generation to catch formatting or content issues.
Ensuring prompts are clear and free of spelling mistakes.
Fixing prompt structures in real-time based on the outputs observed.