Hi everyone, I’ve been working on fine-tuning a GPT model (using gpt-4o-2024-08-06
) with company-specific data stored in a blog-like format in our database. For the fine-tuning process, I used 5 blog posts from our database and passed their titles and bodies as input for training.
The fine-tuning process completed successfully, and I’ve started using the model for prompting. However, when I ask questions, the responses often don’t align with the data I provided during fine-tuning. It seems like the model is not accurately reflecting the content of my dataset.
Could the issue be related to the limited dataset size, or might there be other factors at play? What can I do to ensure the model gives responses based on the data I supplied during fine-tuning? Any tips or insights would be greatly appreciated!