| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: DaMedSum-large |
| results: [] |
| pipeline_tag: summarization |
| language: |
| - da |
| --- |
| |
| ``` |
| _____ ______ __ __ ______ _____ ______ __ __ __ __ |
| /\ __-. /\ __ \ /\ "-./ \ /\ ___\ /\ __-. /\ ___\ /\ \/\ \ /\ "-./ \ |
| \ \ \/\ \\ \ __ \\ \ \-./\ \\ \ __\ \ \ \/\ \\ \___ \\ \ \_\ \\ \ \-./\ \ |
| \ \____- \ \_\ \_\\ \_\ \ \_\\ \_____\\ \____- \/\_____\\ \_____\\ \_\ \ \_\ |
| \/____/ \/_/\/_/ \/_/ \/_/ \/_____/ \/____/ \/_____/ \/_____/ \/_/ \/_/ |
| |
| ``` |
|
|
| ## Model description |
|
|
| This repository contains a model for Danish abstractive summarisation of medical text. |
|
|
| This model is a fine-tuned version of DanSumT5-large 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 |
