sections/finetuning/data.md

For fine-tuning, we use the VQA 2.0 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.