Fine-tuned for classification (discriminative)

The miracle of generative models, such as GPTs, is that they can perform a classification task with the right prompts!In this section, we will fine-tune babbage-002 to classify baseball and hockey text inputs. You will see that you can fine-tune an original OpenAI model to a wide range of tasks. Your imagination will be the limit!Open Fine-tuned_classification.ipynb in the chapter directory in the GitHub repository. The structure of the notebook is the same as Fine_tuning_GPT_3.ipynb notebook we just created. The main section titles are identical.Fine_tuning_GPT_3.ipynb was created for completion tasks with text as a prompt and completion, although you can modify it for any other NLP task. Fine-tuned_classification.ipynb is designed to classify baseball and hockey texts. You can adapt this notebook to other NLP tasks once you have explored it.The dataset is designed for classification tasks, but the process is the same as the one we went...