text: 
  
  TITLE
  Rewrite guides for fine-tuning with Datasets
  
  COMMENTS
  1
  
  REACTIONS
  +1: 0
  -1: 0
  laugh: 0
  hooray: 0
  heart: 0
  rocket: 0
  eyes: 0
  
  BODY
  # 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.