Creating an instruction dataset
In most use cases, creating an instruction dataset is the most difficult part of the fine-tuning process. This is due to multiple factors. Most use cases can be connected to raw text, but it is rare to find natural pairs of instructions and answers. This raw text needs to be transformed into a format that includes both instructions and answers. Moreover, the quality of the data is also crucial. Because of this, a lot of time is invested in manually checking and verifying individual samples. This careful review helps ensure that the dataset is accurate and useful for training the model.
Figure 5.1 – Overview of the post-training data pipeline covered in this chapter
In this section, we will introduce a general framework to create your own instruction datasets, regardless of the final use case. We will then leverage the scraped data from Chapter 3 and transform it into an instruction dataset. The different stages in our data generation...
