# Fine tuning classification example
We will fine-tune a `babbage-002` classifier (replacement for the `ada` models) to distinguish between the two sports: Baseball and Hockey.
## Data exploration
The newsgroup dataset can be loaded using sklearn. First we will look at the data itself:
One sample from the baseball category can be seen above. It is an email to a mailing list. We can observe that we have 1197 examples in total, which are evenly split between the two sports.
## Data Preparation
We transform the dataset into a pandas dataframe, with a column for prompt and completion. The prompt contains the email from the mailing list, and the completion is a name of the sport, either hockey or baseball. For demonstration purposes only and speed of fine-tuning we take only 300 examples. In a real use case the more examples the better the performance.