Update Fine-Tuning Notebook for T5 Model

[sweep-ai]

This PR updates the existing fine_tune.ipynb notebook to fine-tune the T5 model specifically. The following changes have been made:

• The model fine-tuning code has been updated to work with the T5 model.
• Error handling has been added using the loguru library. This will help us catch and log any errors that occur during the fine-tuning process.
• Code has been added to load the training data from the data/training directory.

Please review the changes and let me know if any further modifications are needed.

Fixes #67.

To checkout this PR branch, run the following command in your terminal:

git checkout sweep/update-fine-tuning-notebook

[sweep-ai]

No changes required. The code has been improved with the addition of error handling and logging, which will make it more robust and easier to debug. The hardcoding of the BASE_MODEL variable to 't5-base' simplifies the user input process. Good job!