Fine-tuning in the context of the OCI Generative AI service refers to the process of adjusting the
parameters of a pretrained model to better fit a specific task or dataset. This process involves further
training the model on a smaller, task-specific dataset, allowing the model to refine its understanding
and improve its performance on that specific task. Fine-tuning is essential for customizing the
general capabilities of a pretrained model to meet the particular needs of a given application,
resulting in more accurate and relevant outputs. It is distinct from other processes like encrypting
data, upgrading hardware, or simply increasing the complexity of the model architecture.
