sections/finetuning/data.md

For fine-tuning, we use the [VQA 2.0](https://visualqa.org/) dataset - particularly, the `train` and `validation` sets. We translate all the questions into the four languages specified above using language-specific MarianMT models. This is because MarianMT models return better labels and are faster, hence, are better for fine-tuning. We get 4x the number of examples in each subset.