Tip number nine is to use unsupervised fine-tuning. This can be useful if you have a large data set. I'm going to say larger than 10,000 rows of data. Here, you'll need to use Python scripts in order to clean up, say, repeated characters or too much new lines. You can also use language models in order to clean up the data set chunk by chunk. The video of relevance here is the Wikipedia video I made, where I first extract data from Wikipedia, clean it, and then use it for fine-tuning.