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