
# 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

- 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))

## Results

| Model | BLEU | chrF-3 |
| ------------- | ------------- | ------------- |
| Google en-hu  | 25.30  | 54.08 |
| **BART-base-enhu** | **34.38**  | **58.88** |
| Google hu-en| 34.48  | 59.59 |
| **BART-base-huen** | **38.03** | **61,37** |

## Citation
If you use this model, please cite the following paper:
```
@inproceedings {yang-bart,
    title = {{BARTerezzünk! Messze, messze, messze a világtól, - BART kísérleti modellek magyar nyelvre}},
	booktitle = {XVIII. Magyar Számítógépes Nyelvészeti Konferencia},
	year = {2022},
	publisher = {Szegedi Tudományegyetem, Informatikai Intézet},
	address = {Szeged, Magyarország},
	author = {Yang, Zijian Győző},
	pages = {15--29}
}

```

{"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
* Pretrained on English WikiText-103 and Hungarian Wikipedia
* Finetuned on subcorpora from OPUS


	+ Segments: 56.837.602


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


* tokenized input text (tokenizer: HuSpaCy)


Results
-------


Model: Google en-hu, BLEU: 25.30, chrF-3: 54.08
Model: BART-base-enhu, BLEU: 34.38, chrF-3: 58.88
Model: Google hu-en, BLEU: 34.48, chrF-3: 59.59
Model: BART-base-huen, BLEU: 38.03, chrF-3: 61,37


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 
