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---
language:
- de
library_name: transformers
base_model: google/mT5-base
datasets:
- DEplain/DEplain-APA-sent
metrics:
- sari
- bleu
- bertscore
pipeline_tag: text2text-generation
---
# Model Card for mT5-base-trimmed_deplain-apa
Finetuned mT5-Model for German sentence-level text-simplification.
## Model Details
### Model Description
- **Model type:** Encoder-Decoder-Transformer
- **Language(s) (NLP):** German
- **Finetuned from model:** google/mT5-base
- **Task**: Text-Simplification
## Training Details
### Training Data
[DEplain/DEplain-APA-sent](https://huggingface.co/datasets/DEplain/DEplain-APA-sent) \
Stodden et al. (2023):[arXiv:2305.18939](arXiv:2305.18939)
### Training Procedure
Parameter-efficient Fine-Tuning with LoRA. Vocabulary trimmed to 32.000 most frequent tokens for German.
#### Training Hyperparameters
* Batch Size: 16
* Epochs: 1
* Learning Rate: 0.001
* Optimizer: Adafactor
#### LoRA Hyperparameters
* R: 32
* Alpha: 64
* Dropout: 0.1
* Target modules: all linear layers |