Opus-mt-eng-nor Open-source Machine Translation Model - Achieve Accurate English to Norwegian Translation for Free

Opus Mt Eng Nor

Developed by jkorsvik

This is a Transformer-based machine translation model from English to Norwegian (including Bokmål and Nynorsk), released by Tatoeba-Challenge.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Multi-dialect Norwegian support #High BLEU score translation #Back-translation data augmentation

Downloads 18

Release Time : 1/23/2023

Model Overview

This model is used to translate English text into Norwegian (including both Bokmål and Nynorsk variants), trained on the OPUS dataset with support for multiple Norwegian dialects.

Model Features

Multi-dialect Support

Supports both official written forms of Norwegian: Bokmål and Nynorsk

Large-scale Training Data

Utilizes over 11 million sentence pairs from the Tatoeba dataset along with high-quality corpora like Wikipedia and Wikiquote

Preprocessing Optimization

Employs standardization and SentencePiece tokenization (spm32k) for text preprocessing

Model Capabilities

English to Norwegian translation

Bokmål output support

Nynorsk output support

Formal text translation

Informal text translation

Use Cases

Content Localization

Wikipedia Content Translation

Translate English Wikipedia articles into Norwegian versions

Wikipedia corpus already used in training data

Educational Applications

Language Learning Assistance

Provide Norwegian translation references for English learners

🚀 eng-nor

This project focuses on English to Norwegian translation, offering a high - quality translation solution.
It provides detailed information about the model, training data, test results, and system information.

✨ Features

Supports translation from English to two Norwegian variants: Bokmål (nb) and Nynorsk (nn).
Utilizes the transformer - align model for translation tasks.
Comes with pre - processing steps including normalization and SentencePiece.

📦 Installation

No installation steps are provided in the original document.

📚 Documentation

Model Information

Property	Details
Source Language Name	English
Target Language Name	Norwegian
OPUS Readme	README.md
Model Type	transformer-align
Source Language Code	en
Target Language Codes	nb, nn
Dataset	opus with backtranslations
Release Date	2021 - 04 - 20
Pre - processing	normalization + SentencePiece (spm32k,spm32k)
Download Original Weights	opus+bt-2021-04-20.zip

Training Data

eng - nno: Tatoeba - train (1661769), wikipedia.aa.nno - eng (995603), wikipedia.ab.nno - eng (605107), wikiquote.aa.nno - eng (22626)
eng - nob: Tatoeba - train (11525999), wikibooks.aa.nob - eng (37901), wikinews.aa.nob - eng (8706), wikipedia.aa.nob - eng (992563), wikipedia.ab.nob - eng (992772), wikipedia.ac.nob - eng (992621), wikipedia.ad.nob - eng (992828), wikipedia.ae.nob - eng (992812), wikipedia.af.nob - eng (976715), wikiquote.aa.nob - eng (10443), wikisource.aa.nob - eng (279891)

Validation Data

eng - nno: Tatoeba - dev, 505
eng - nob: Tatoeba - dev, 5189
total - size - shuffled: 1505
devset - selected: top 1505 lines of Tatoeba - dev.src.shuffled

Test Data

Tatoeba - test.eng - nno: 460/3428
Tatoeba - test.eng - nob: 4539/36110
Tatoeba - test.eng - nor: 4999/39547
Test set translations file: test.txt
Test set scores file: eval.txt

Test Scores

BLEU - scores

Test set	score
Tatoeba - test.eng - nob	56.4
Tatoeba - test.eng - nor	55.4
Tatoeba - test.eng - nno	40.3

chr - F - scores

Test set	score
Tatoeba - test.eng - nob	0.716
Tatoeba - test.eng - nor	0.71
Tatoeba - test.eng - nno	0.615

System Info

Property	Details
hf_name	eng - nor
source_languages	en
target_languages	nb, nn
opus_readme_url	https://object.pouta.csc.fi/Tatoeba-MT-models/eng-nor/opus+bt-2021-04-20.zip/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['en', 'nb', 'nn']
src_constituents	['eng']
tgt_constituents	['nob', 'nno']
src_multilingual	False
tgt_multilingual	True
helsinki_git_sha	59400fea592520766f9910390155681bc930dbc4
transformers_git_sha	fd5cdaeea6eafac32e9d967327bfa3dc0e0d962d
port_machine	DESKTOP - 6CPR2HH
port_time	2023 - 01 - 23 - 21:07

📄 License

This project is licensed under the Apache - 2.0 license.

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