
# LayoutXLM Model Fine-tuned with CIVQA and DVQA dataset

This is a fine-tuned version of the [LayoutXLM model](https://huggingface.co/microsoft/layoutxlm-base), which was trained on Czech Invoice Visual Question Answering (CIVQA) dataset containing invoices in the Czech language as well as on the Data Visualizations via Question Answering ([DVQA] (https://paperswithcode.com/dataset/dvqa)) dataset.

This model enables Document Visual Question Answering on Czech invoices with the use of the existing DVQA dataset.

Regarding the Czech invoices, we focused on 10 different entities, which are crucial for processing the invoices.
- Variable symbol
- Specific symbol
- Constant symbol
- Bank code
- Account number
- Total amount
- Invoice date
- Name of supplier
- DIC
- QR code

You can find more information about this model in this [paper](https://nlp.fi.muni.cz/raslan/raslan23.pdf#page=31).
{"language": ["cs"], "license": "mit", "tags": ["document question answering"]}
transformers pytorch layoutlmv2 document-question-answering document question answering cs license:mit endpoints_compatible region:us