Opus-mt-es-en Open-source Machine Translation Model - Free and Accurate Spanish-English Translation

Opus Mt Es En

Developed by Helsinki-NLP

This is a machine translation model from Spanish to English based on the Transformer architecture, developed by the Helsinki-NLP team.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Spanish-English Translation #Transformer Architecture #SentencePiece Tokenization

Downloads 385.40k

Release Time : 3/2/2022

Model Overview

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

Model Features

High-Performance Translation

Excellent performance on multiple test sets, achieving a BLEU score of up to 59.6.

Standardized Preprocessing

Uses standardized preprocessing and SentencePiece tokenization to improve translation quality.

Multi-Test Set Validation

Validated on multiple news test sets and the Tatoeba test set, demonstrating stable performance.

Model Capabilities

Spanish to English text translation

Supports standardized text input

Supports SentencePiece tokenization

Use Cases

Text Translation

News Translation

Translate Spanish news into English

Achieved a BLEU score of 27.9 on the news-test2008 test set

Daily Conversation Translation

Translate Spanish daily conversations into English

Achieved a BLEU score of 59.6 on the Tatoeba test set

🚀 spa-eng Translation Model

This is a Spanish-to-English translation model. It uses the Transformer architecture and provides high - quality translation capabilities. The model comes with pre - processing steps and offers various evaluation metrics.

🚀 Quick Start

The spa-eng model is designed for translating Spanish text into English. You can download the original weights and test set translations from the provided links.

✨ Features

Language Pair: Translates from Spanish (spa) to English (eng).
Model Architecture: Utilizes the Transformer model.
Pre - processing: Applies normalization and SentencePiece (spm32k, spm32k).

📦 Installation

There is no specific installation command provided in the original document. If you want to use this model, you can download the original weights from opus - 2020 - 08 - 18.zip.

📚 Documentation

Model Information

Property	Details
Model Type	Transformer
Source Languages	spa
Target Languages	eng
Pre - processing	normalization + SentencePiece (spm32k, spm32k)
Download Original Weights	opus-2020-08-18.zip
Test Set Translations	opus-2020-08-18.test.txt
Test Set Scores	opus-2020-08-18.eval.txt
OPUS Readme	spa-eng

Benchmarks

testset	BLEU	chr - F
newssyscomb2009 - spaeng.spa.eng	30.6	0.570
news - test2008 - spaeng.spa.eng	27.9	0.553
newstest2009 - spaeng.spa.eng	30.4	0.572
newstest2010 - spaeng.spa.eng	36.1	0.614
newstest2011 - spaeng.spa.eng	34.2	0.599
newstest2012 - spaeng.spa.eng	37.9	0.624
newstest2013 - spaeng.spa.eng	35.3	0.609
Tatoeba - test.spa.eng	59.6	0.739

System Info

hf_name: spa - eng
source_languages: spa
target_languages: eng
opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-eng/README.md
original_repo: Tatoeba - Challenge
tags: ['translation']
languages: ['es', 'en']
src_constituents: {'spa'}
tgt_constituents: {'eng'}
src_multilingual: False
tgt_multilingual: False
prepro: normalization + SentencePiece (spm32k, spm32k)
url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/spa-eng/opus-2020-08-18.zip
url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/spa-eng/opus-2020-08-18.test.txt
src_alpha3: spa
tgt_alpha3: eng
short_pair: es - en
chrF2_score: 0.7390000000000001
bleu: 59.6
brevity_penalty: 0.9740000000000001
ref_len: 79376.0
src_name: Spanish
tgt_name: English
train_date: 2020 - 08 - 18 00:00:00
src_alpha2: es
tgt_alpha2: en
prefer_old: False
long_pair: spa - eng
helsinki_git_sha: d2f0910c89026c34a44e331e785dec1e0faa7b82
transformers_git_sha: f7af09b4524b784d67ae8526f0e2fcc6f5ed0de9
port_machine: brutasse
port_time: 2020 - 08 - 24 - 18:20

📄 License

This project is licensed under the Apache - 2.0 license.

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