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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: DaMedSum-base
results: []
language:
- da
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
```
_____ ______ __ __ ______ _____ ______ __ __ __ __
/\ __-. /\ __ \ /\ "-./ \ /\ ___\ /\ __-. /\ ___\ /\ \/\ \ /\ "-./ \
\ \ \/\ \\ \ __ \\ \ \-./\ \\ \ __\ \ \ \/\ \\ \___ \\ \ \_\ \\ \ \-./\ \
\ \____- \ \_\ \_\\ \_\ \ \_\\ \_____\\ \____- \/\_____\\ \_____\\ \_\ \ \_\
\/____/ \/_/\/_/ \/_/ \/_/ \/_____/ \/____/ \/_____/ \/_____/ \/_/ \/_/
```
## Model description
This repository contains a model for Danish abstractive summarisation of medicaltext.
This model is a fine-tuned version of DanSumT5-base trained on a danish medical text dataset.
The model was trained on LUMI using 1 AMD MI250X GPU.
## Authors
Nicolaj Larsen
Mikkel Kildeberg
Emil Schledermann
### Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1+git7548e2f
- Datasets 2.13.2
- Tokenizers 0.13.3 |