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README.md

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+---
+language: de
+tags:
+- summarization
+datasets:
+- mlsum
+---
+
+# mT5-small fine-tuned on German MLSUM
+This model was finetuned for 3 epochs with a max_len (input) of 768 tokens and target_max_len of 192 tokens.  
+It was fine-tuned on all German articles present in the train split of the [MLSUM dataset](https://huggingface.co/datasets/mlsum) having less than 384 "words" after splitting on whitespace, which resulted in 80249 articles.  
+The exact expression to filter the dataset was the following:
+```python
+dataset = dataset.filter(lambda e: len(e['text'].split()) < 384)
+```
+
+## Evaluation results
+The fine-tuned model was evaluated on 2000 random articles from the validation set.
+Mean [f1 ROUGE scores](https://github.com/pltrdy/rouge) were calculated for both the fine-tuned model and the lead-3 baseline (which simply produces the leading three sentences of the document) and are presented in the following table.
+
+| Model         | Rouge-1 | Rouge-2  | Rouge-L |
+| ------------- |:-------:| --------:| -------:|
+| mt5-small     | 0.399   | 0.318    | 0.392   |
+| lead-3        | 0.343   | 0.263    | 0.341   |