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# German Medical BERT
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This is a fine-tuned model on the Medical domain for the German language and based on German BERT. This model has only been trained to improve on-target
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## Overview
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**Language model:** bert-base-german-cased
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- With standard parameter settings for fine-tuning as mentioned in the original BERT paper.
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- Although had to train for up to 25 epochs for classification.
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## Performance (Micro precision, recall and f1 score for multilabel code classification)
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|Models\\\\\\\\t\\\\\\\\t\\\\\\\\t|P\\\\\\\\t|R\\\\\\\\t|F1\\\\\\\\t|
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|:--------------\\\\\\\\t|:------|:------|:------|
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|German BERT\\\\\\\\t\\\\\\\\t|86.04\\\\\\\\t|75.82\\\\\\\\t|80.60\\\\\\\\t|
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|German MedBERT-256\\\\\\\\t|87.41\\\\\\\\t|77.97\\\\\\\\t|82.42\\\\\\\\t|
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|German MedBERT-512\\\\\\\\t|87.75\\\\\\\\t|78.26\\\\\\\\t|82.73\\\\\\\\t|
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## Author
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Manjil Shrestha: `shresthamanjil21 [at] gmail.com`
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## Related Paper:
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[Report](https://opus4.kobv.de/opus4-rhein-waal/frontdoor/index/index/searchtype/collection/id/16225/start/0/rows/10/doctypefq/masterthesis/docId/740)
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Get in touch:
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[LinkedIn](https://www.linkedin.com/in/manjil-shrestha-038527b4/)
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# German Medical BERT
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This is a fine-tuned model on the Medical domain for the German language and based on German BERT. This model has only been trained to improve on-target tasks (Masked Language Model). It can later be used to perform a downstream task of your needs, while I performed it for the NTS-ICD-10 text classification task.
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## Overview
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**Language model:** bert-base-german-cased
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- With standard parameter settings for fine-tuning as mentioned in the original BERT paper.
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- Although had to train for up to 25 epochs for classification.
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## Performance (Micro precision, recall, and f1 score for multilabel code classification)
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|Models|P|R|F1|
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|:------|:------|:------|:------|
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|German BERT|86.04|75.82|80.60|
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|German MedBERT-256 (fine-tuned)|87.41|77.97|82.42|
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|German MedBERT-512 (fine-tuned)|87.75|78.26|82.73|
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## Author
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Manjil Shrestha: `shresthamanjil21 [at] gmail.com`
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## Related Paper: [Report](https://opus4.kobv.de/opus4-rhein-waal/frontdoor/index/index/searchtype/collection/id/16225/start/0/rows/10/doctypefq/masterthesis/docId/740)
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Get in touch:
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[LinkedIn](https://www.linkedin.com/in/manjil-shrestha-038527b4/)
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