
# BART Translation model

For further models, scripts and details, see [our repository](https://github.com/nytud/machine-translation) or [our demo site](https://juniper.nytud.hu/demo/nlp).

- Source language: English
- Target language: Hungarian

- BART base model:
  - Pretrained on English WikiText-103 and Hungarian Wikipedia
  - Finetuned on subcorpora from OPUS
  	- Segments: 56.837.602

## Limitations

- tokenized input text (tokenizer: [HuSpaCy](https://huggingface.co/huspacy))
- max_source_length = 128
- max_target_length = 128

## Results

| Model | BLEU | chrF-3 | chrF-6 |
| ------------- | ------------- | ------------- | ------------- |
| Google | 25.30 | 54.09 | 49.0 |
| **BART** | **36.89** | **60.77** | **56.4** |
| mT5 | 27.69  | 53.73 | 48.57 |

## Citation
If you use this model, please cite the following paper:
```
@inproceedings {laki-yang-mt,
    title = {{Jobban fordítunk magyarra, mint a Google!}},
	booktitle = {XVIII. Magyar Számítógépes Nyelvészeti Konferencia},
	year = {2022},
	publisher = {Szegedi Tudományegyetem, Informatikai Intézet},
	address = {Szeged, Magyarország},
	author = {Laki, László and Yang, Zijian Győző},
	pages = {357--372}
}

```
{"language": ["en", "hu"], "license": "apache-2.0", "tags": ["translation"], "metrics": ["sacrebleu", "chrf"], "widget": [{"text": "This may not make much sense to you, sir, but I'd like to ask your permission to date your daughter.", "example_title": "Translation: English-Hungarian"}]}
transformers pytorch bart text2text-generation translation en hu license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #translation #en #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

BART Translation model
======================


For further models, scripts and details, see our repository or our demo site.


* Source language: English
* Target language: Hungarian
* BART base model:


	+ Pretrained on English WikiText-103 and Hungarian Wikipedia
	+ Finetuned on subcorpora from OPUS
		- Segments: 56.837.602


Limitations
-----------


* tokenized input text (tokenizer: HuSpaCy)
* max\_source\_length = 128
* max\_target\_length = 128


Results
-------



If you use this model, please cite the following paper:



TAGS
#transformers #pytorch #bart #text2text-generation #translation #en #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bart #text2text-generation #translation #en #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
