README.md

---
license: mit
---
---
license: mit
---

**Descrición do Modelo** 

Modelo feito con OpenNMT para o par español-galego utilizando unha arquitectura transformer. 

**Como utilizar**

+ Abrir terminal bash
+ Instalar [Python 3.9](https://www.python.org/downloads/release/python-390/)
+ Instalar [Open NMT toolkit v.2.2](https://github.com/OpenNMT/OpenNMT-py)
+ Traducir un input_text utilizando o modelo NOS-MT-en-gl co seguinte comando:

```bash 
onmt_translate -src input_text -model NOS-MT-es-gl -output ./output_file.txt -replace_unk -phrase_table phrase_table-es-gl.txt -gpu 0
```
+ O resultado da tradución estará no PATH indicado no flag -output.

**Adestramento**

Datos utilizados para o adestramento

Auténticos e Sintéticos (Transliteração)[Colocar Paper] 

**Procedemento de adestramento**

Tokenization feita co tokenizador de linguakit https://github.com/citiususc/Linguakit

BPE 

**Hiperparámetros** 

Colocar o yaml para cada um dos pares 

**Avaliación** 
A avalación dos modelos é feita cunha mistura de tests desenvolvidos internamente
(gold1, gold2, test-suite) con outros datasets disponíbeis en galego (Flores).

| GOLD 1        | GOLD 2        | FLORES  | TEST-SUITE|
| ------------- |:-------------:| -------:|----------:| 
| 36.8          | 47.1          | 32.3    | 42.7      |



**Información adicional** 

Licensing information 

Apache License, Version 2.0 

**Financiamento** 

Financiamento

This research was funded by the project "Nós: Galician in the society and economy of artificial intelligence", agreement between Xunta de Galicia and University of Santiago de Compostela, and grant ED431G2019/04 by the Galician Ministry of Education, University and Professional Training, and the European Regional Development Fund (ERDF/FEDER program), and Groups of Reference: ED431C 2020/21.

**Citation Information**

@article{, 
  title={}, 
  author={}, 
  year={2022}, 
  url={} 
}