Rewrite guides for fine-tuning with Datasets
# What does this PR do?

This PR updates the current documentation for [Fine-tuning with custom datasets](https://huggingface.co/transformers/custom_datasets.html#). It removes the custom code for loading a dataset in favor of using the Datasets library for loading and preprocessing a dataset. The new guide also introduces the Keras method for compiling and fitting a model instead of using `TFTrainingArguments` and `TFTrainer`.

⚠️ The TensorFlow example for Question Answering still needs a little work. It returns `ValueError: No gradients provided for any variable` when calling `model.fit`.  @Rocketknight1 has provided a temporary solution where we set `dummy_labels=True` in `tf_to_dataset`.

This [notebook](https://drive.google.com/file/d/1irNIGeRtfUb-4x79ZBloNy49m_FW-sOy/view?usp=sharing) contains all the code examples shown in the guide.

# To do:

- [ ] Update the TensorFlow code example for question answering once we have a better solution.
Thank you, @stevhliu!