| | --- |
| | license: mit |
| | language: |
| | - cs |
| | tags: |
| | - document question answering |
| | --- |
| | |
| | # LayoutLMv3 Model Fine-tuned with CIVQA (Tesseract) dataset |
| |
|
| | This is a fine-tuned version of the [LayoutLMv3 model](https://huggingface.co/microsoft/layoutlmv3-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). |
