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| license: mit |
| language: |
| - cs |
| tags: |
| - document question answering |
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| # LayoutLMv2 Model Fine-tuned with CIVQA (Tesseract) dataset |
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| This is a fine-tuned version of the [LayoutLMv2 model](https://huggingface.co/microsoft/layoutlmv2-base-uncased), 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. |
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| This model enables Document Visual Question Answering on Czech invoices with the use of the existing DVQA dataset. |
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| 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 |
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| You can find more information about this model in this [paper](https://nlp.fi.muni.cz/raslan/raslan23.pdf#page=31). |
