Preparing Your Dataset for Fine-Tuning

Once we are ready to fine-tune using the OpenAI API, we'll need to acquire and prepare the data we will use for the fine-tuning.

Acquiring our dataset

Before we start fine-tuning a model with the OpenAI API, it's important to get a suitable dataset and have a good understanding of it. The dataset we choose should align well with the goals of our project. For instance, if we aim to fine-tune a model to generate medical text, a dataset filled with medical journals or articles would be needed. The right dataset forms the foundation upon which the fine-tuning process is built, making its selection a critical step.

The quality of the data we acquire is as important as the quantity. A high-quality dataset is one that is rich in relevant information, well-organized, and free from errors or inconsistencies. On the other hand, the quantity refers to the size of the dataset, which should be substantial enough to cover a wide range of scenarios and examples within ...