ChatGPT-Integration-PoC-Testing

In this example, we load the movie review dataset into a Pandas dataframe and split it into training and validation sets. We then fine-tune the GPT-3 model on the training data by generating a summary for each movie review and saving it to the training data. After training, we evaluate the model on the validation data by generating a summary for each movie review and comparing it to the actual summary. The accuracy of the model is calculated and displayed as output. This is just one example of how you can fine-tune a GPT-3 model for a specific task. You can fine-tune the model further by changing the hyperparameters, such as the temperature, and by using a different model or dataset as required.