Donut 🍩, Document understanding transformer, is a new method of document understanding
that utilizes an OCR-free end-to-end Transformer model. Donut does not require off-the-shelf OCR
engines/APIs, yet it shows state-of-the-art performances on various visual document understanding tasks,
such as visual document classification or information extraction (a.k.a. document parsing).
Intended uses & limitations
Basic Donut model
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
