Create README_English.md

README_English.md

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+---
+license: mit
+language:
+- gl
+metrics:
+- bleu (Gold1): 82.6
+- bleu (Gold2): 49.9
+- bleu (Flores): 23.8 
+- bleu (Test-suite): 77.2 
+---
+
+---
+License: MIT
+---
+
+**Model Description** 
+
+OpenNMT model for English-Galician 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-gl-es model with the following command:
+
+```bash 
+onmt_translate -src input_text -model NOS-MT-gl-es.pt -output ./output_file.txt -replace_unk -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 [ProxectoNós](https://github.com/proxectonos/corpora). The former are corpora of translations directly produced by human translators. The latter are corpora of English-Portuguese translations, which we have converted into English-Galician by means of Portuguese-Galician translation with Opentrad/Apertium and transliteration for out-of-vocabulary words. 
+
+**Training process**
+
++ Tokenization of the datasets made with linguakit tokeniser https://github.com/citiususc/Linguakit
++ The vocabulary for the models was generated through the script [learn_bpe.py](https://github.com/OpenNMT/OpenNMT-py/blob/master/tools/learn_bpe.py) of OpenNMT
++ Using .yaml in this repository you can replicate the training process as follows
+
+```bash 
+onmt_build_vocab -config  bpe-gl-es_emb.yaml -n_sample 100000
+onmt_train -config bpe-gl-es_emb.yaml
+```
+
+**Hyper-parameters** 
+
+The parameters used for the development of the model can be directly consulted in the same .yaml file bpe-en-gl_emb.yaml 
+
+**Evaluation** 
+
+The BLEU evaluation of the models is made with a mixture of internally developed tests (gold1, gold2, test-suite) and other datasets available in Galician (Flores).
+
+| GOLD 1        | GOLD 2        | FLORES  | TEST-SUITE|
+| ------------- |:-------------:| -------:|----------:| 
+| 82.6          | 49.9          | 23.8    | 77.2      |
+
+
+**Licensing information** 
+
+MIT License
+
+Copyright (c) 2023 Proxecto Nós
+
+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 "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**
+
+Gamallo, Pablo; Bardanca, Daniel; Pichel, José Ramom; García, Marcos; Rodríguez-Rey, Sandra; de-Dios-Flores, Iria. 2023. NOS-MT-OpenNMT-gl-es. Url: https://huggingface.co/proxectonos/NOS-MT-OpenNMT-gl-es