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---
license: mit
language:
- gl
metrics:
- bleu (Gold1): 79.6
- bleu (Gold2): 43.3
- bleu (Flores): 21.8
- bleu (Test-suite): 74.3
---
**Model description**
Model developed with OpenNMT for the Spanish-Galician pair using a transformer architecture.
**How to translate**
+ Open bash terminal
+ Install [Python 3.9](https://www.python.org/downloads/release/python-390/)
+ Install [Open NMT toolkit v.2.2](https://github.com/OpenNMT/OpenNMT-py)
+ Translate an input_text using the NOS-MT-en-gl model with the following command:
```bash
onmt_translate -src input_text聽-model NOS-MT-es-gl -output ./output_file.txt -replace_unk -phrase_table phrase_table-es-gl.txt -gpu 0
```
+ The result of the translation will be in the PATH indicated by the -output flag.
**Training**
In the training we have used authentic and synthetic corpora from [ProxectoN贸s](https://github.com/proxectonos/corpora). The former are corpora of translations directly produced by human translators. The latter are corpora of Spanish-Portuguese translations, which we have converted into Spanish-Galician by means of Portuguese-Galician translation with Opentrad/Apertium and transliteration for out-of-vocabulary words.
**Training process**
+ Tokenisation of the datasets made with LinguaKit tokeniser https://github.com/citiususc/Linguakit
+ Vocabulary for the models was created by the script [learn_bpe.py](https://github.com/OpenNMT/OpenNMT-py/blob/master/tools/learn_bpe.py) of OpenNMT
+ Using the .yaml in this repository you can replicate the training process as follows
```bash
onmt_build_vocab -config bpe-es-gl_emb.yaml -n_sample 100000
onmt_train -config bpe-es-gl_emb.yaml
```
**Hyper-parameters**
The parameters used for the development of the model can be directly viewed in the same .yaml file bpe-es-gl_emb.yaml
**Evaluation**
The BLEU evaluation of the models is done by mixing internally developed tests (gold1, gold2, test-suite) and other datasets available in Galician (Flores).
| GOLD 1 | GOLD 2 | FLORES | TEST-SUITE|
| ------------- |:-------------:| -------:|----------:|
| 79.6 | 43.3 | 21.8 | 74.3 |
**Licensing information**
MIT License
Copyright (c) 2023 Proxecto N贸s
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
**Funding**
This research was funded by the project "N贸s: 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**
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