pytorch encoder-decoder seq2seq fa transformers license:apache-2.0 summarization text2text-generation
.gitattributes README.md config.json pytorch_model.bin special_tokens_map.json tokenizer_config.json vocab.txt
---
language: fa
license: apache-2.0
tags:
- summarization
---

A Bert2Bert model on the Wiki Summary dataset to summarize articles. The model achieved an 8.47 ROUGE-2 score. 
 
For more detail, please follow the [Wiki Summary](https://github.com/m3hrdadfi/wiki-summary) repo. 


## Eval results
The following table summarizes the ROUGE scores obtained by the Bert2Bert model.

|    %    | Precision | Recall | FMeasure |
|:-------:|:---------:|:------:|:--------:|
| ROUGE-1 |   28.14   |  30.86 |   27.34  |
| ROUGE-2 |   07.12   | 08.47* |   07.10  |
| ROUGE-L |   28.49   |  25.87 |   25.50  |


## Questions?
Post a Github issue on the [Wiki Summary](https://github.com/m3hrdadfi/wiki-summary/issues) repo.
