
# mT5 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 model used: mT5-small
- Finetuned on subcorpora from OPUS
	- Segments: 56.837.602
- prefix: "translate English to Hungarian: "


## 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 en-hu  | 25.30  | 54.08 | 49.06 |
| 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": "translate English to Hungarian: This may not make much sense to you, sir, but I'd like to ask your permission to date your daughter."}]}
transformers pytorch mt5 text2text-generation translation en hu license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #translation #en #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mT5 Translation model
=====================


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


* Source language: English
* Target language: Hungarian
* Pretrained model used: mT5-small
* Finetuned on subcorpora from OPUS


	+ Segments: 56.837.602
* prefix: "translate English to Hungarian: "


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 #mt5 #text2text-generation #translation #en #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

passage: TAGS
#transformers #pytorch #mt5 #text2text-generation #translation #en #hu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
