# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->

This model card aims to be a baseline model for using RVL-CDIP with Donut. The model has been trained on small scale dataset of RVL-CDIP (specically 100 images from this dataset).

## Model Details

The model using Donut with VisionEncoderDecoder and Transformers as the backbone model for an end-to-end Document Classification task

### Downstream Use [optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->

This model can be use for fine-tuning task related Document Classification in different area like Food Document, Financial Document, etc.
For further task downstream fine-tune, please related to the orignal model from Naver.



{"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["DocumentAI", "ImageClassification", "Donut"], "datasets": ["sitloboi2012/rvl_cdip_small_dataset", "sitloboi2012/rvl_cdip_large_dataset"], "metrics": ["accuracy"], "pipeline_tag": "image-to-text"}
transformers pytorch vision-encoder-decoder DocumentAI ImageClassification Donut image-to-text en dataset:sitloboi2012/rvl_cdip_small_dataset dataset:sitloboi2012/rvl_cdip_large_dataset license:apache-2.0 endpoints_compatible region:us