transformers pytorch mbart text2text-generation text simplification plain language easy-to-read language sentence simplification de dataset:DEplain/DEplain-APA-sent dataset:DEplain/DEplain-web-sent arxiv:2305.18939 autotrain_compatible endpoints_compatible region:us
---
datasets:
- DEplain/DEplain-APA-sent
- DEplain/DEplain-web-sent
language:
- de
library_name: transformers
metrics:
- sari
- bleu
- bertscore
pipeline_tag: text2text-generation
tags:
- text simplification
- plain language
- easy-to-read language
- sentence simplification
---

# DEplain German Text Simplification

This model belongs to the experiments done at the work of Stodden, Momen, Kallmeyer (2023). ["DEplain: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification."](https://arxiv.org/abs/2305.18939) In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Toronto, Canada. Association for Computational Linguistics. 
Detailed documentation can be found on this GitHub repository [https://github.com/rstodden/DEPlain](https://github.com/rstodden/DEPlain)

### Model Description

The model is a finetuned checkpoint of the pre-trained mBART model `mbart-large-cc25`. With a trimmed vocabulary to the most frequent 30k words in the German language. 

The model was finetuned towards the task of German text simplification of sentences.

The finetuning dataset included manually aligned sentences from the datasets `DEplain-APA-sent` and `DEplain-web-sent-manual-open`
