Opus-MT-En-Hy Open Source Translation Model - Achieve Accurate English to Armenian Translation for Free

Opus Mt En Hy

Developed by Helsinki-NLP

This is an English-to-Armenian machine translation model based on the transformer-align architecture, developed by the Helsinki-NLP team.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #English-Armenian Translation #Low-Resource Language Support #SentencePiece Preprocessing

Downloads 99

Release Time : 3/2/2022

Model Overview

This model is specifically designed for translating English text into Armenian, utilizing standardized preprocessing and SentencePiece tokenization techniques.

Model Features

Multilingual Support

Supports translation tasks from English to Armenian.

Standardized Preprocessing

Employs standardized and SentencePiece tokenization techniques for text preprocessing.

Transformer Architecture

Based on the transformer-align architecture, providing better translation quality.

Model Capabilities

English-to-Armenian text translation

Supports standardized text processing

Use Cases

Language Services

Document Translation

Translate English documents into Armenian

Achieved a BLEU score of 16.6 on the Tatoeba test set.

Cross-Language Communication

Facilitates communication between English and Armenian speakers

🚀 eng-hye Translation Model

This is a translation model designed for translating English to Armenian. It provides a reliable solution for language conversion between these two languages.

🚀 Quick Start

This model is used for translating English to Armenian. You can download the original weights and test set translations through the following links:

Download original weights: opus-2020-06-16.zip
Test set translations: opus-2020-06-16.test.txt
Test set scores: opus-2020-06-16.eval.txt

✨ Features

Source and Target Languages: The source language is English (eng), and the target language is Armenian (hye).
Model Type: It uses the transformer-align model.
Pre - processing: The pre - processing includes normalization and SentencePiece (spm4k, spm4k).

📚 Documentation

Model Details

Property	Details
Model Type	transformer-align
Source Language	English (`eng`)
Target Language	Armenian (`hye`)
Pre - processing	normalization + SentencePiece (spm4k, spm4k)
Download Link for Original Weights	opus-2020-06-16.zip
Test Set Translations Link	opus-2020-06-16.test.txt
Test Set Scores Link	opus-2020-06-16.eval.txt

Benchmarks

testset	BLEU	chr-F
Tatoeba-test.eng.hye	16.6	0.404

System Info

hf_name: eng-hye
source_languages: eng
target_languages: hye
opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-hye/README.md
original_repo: Tatoeba-Challenge
tags: ['translation']
languages: ['en', 'hy']
src_constituents: {'eng'}
tgt_constituents: {'hye', 'hye_Latn'}
src_multilingual: False
tgt_multilingual: False
prepro: normalization + SentencePiece (spm4k, spm4k)
url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hye/opus-2020-06-16.zip
url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hye/opus-2020-06-16.test.txt
src_alpha3: eng
tgt_alpha3: hye
short_pair: en-hy
chrF2_score: 0.40399999999999997
bleu: 16.6
brevity_penalty: 1.0
ref_len: 5115.0
src_name: English
tgt_name: Armenian
train_date: 2020 - 06 - 16
src_alpha2: en
tgt_alpha2: hy
prefer_old: False
long_pair: eng-hye
helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine: brutasse
port_time: 2020 - 08 - 21 - 14:41

📄 License

This project is licensed under the Apache-2.0 license.

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