Opus-mt-tl-en Open-Source Machine Translation Model - Supports Fast and Accurate Translation from Filipino to English

Opus Mt Tl En

Developed by Helsinki-NLP

A Transformer-based machine translation model for Filipino to English, developed by the Helsinki-NLP team, supporting translation from Filipino written in Latin script to English.

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Low-resource language translation #SentencePiece tokenization #Tatoeba corpus training

Downloads 13.99k

Release Time : 3/2/2022

Model Overview

This model is specifically designed for translating Filipino text written in Latin script into English, utilizing Transformer architecture and SentencePiece tokenization technology, suitable for basic text translation needs.

Model Features

Standardized preprocessing

Uses standardized preprocessing and SentencePiece tokenization (spm32k) to ensure translation quality.

Specific language support

Optimized specifically for translation from Filipino written in Latin script (tgl_Latn) to English (eng).

Open-source license

Released under Apache-2.0 license, allowing free use for both commercial and research purposes.

Model Capabilities

Filipino to English text translation

Latin script text processing

Use Cases

Language learning

Filipino learning aid

Helps English speakers understand Filipino text content

Provides basic translation support

Basic translation needs

Simple text translation

Translates simple Filipino sentences or paragraphs into English

BLEU 35.0, chr-F 0.542

🚀 tgl-eng Translation Model

This is a translation model focusing on translating from Tagalog to English, offering reliable translation capabilities and performance metrics.

🚀 Quick Start

The tgl-eng model is designed for translating Tagalog text into English. You can download the original weights and test set translations from the provided links to evaluate the model's performance.

✨ Features

Language Pair: Specifically tailored for the Tagalog - English language pair.
Model Type: Utilizes the transformer-align model.
Pre - processing: Applies normalization and SentencePiece (spm32k, spm32k) for pre - processing.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

No code examples are provided in the original document.

📚 Documentation

Model Information

Source Group: Tagalog
Target Group: English
OPUS Readme: tgl - eng
Model: transformer - align
Source Language(s): tgl_Latn
Target Language(s): eng
Pre - processing: normalization + SentencePiece (spm32k, spm32k)
Download Original Weights: opus - 2020 - 06 - 17.zip
Test Set Translations: opus - 2020 - 06 - 17.test.txt
Test Set Scores: opus - 2020 - 06 - 17.eval.txt

Benchmarks

Testset	BLEU	chr - F
Tatoeba - test.tgl.eng	35.0	0.542

System Info

Property	Details
hf_name	tgl - eng
source_languages	tgl
target_languages	eng
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/tgl-eng/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['tl', 'en']
src_constituents	{'tgl_Latn'}
tgt_constituents	{'eng'}
src_multilingual	False
tgt_multilingual	False
prepro	normalization + SentencePiece (spm32k, spm32k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/tgl-eng/opus-2020-06-17.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/tgl-eng/opus-2020-06-17.test.txt
src_alpha3	tgl
tgt_alpha3	eng
short_pair	tl - en
chrF2_score	0.542
bleu	35.0
brevity_penalty	0.975
ref_len	18168.0
src_name	Tagalog
tgt_name	English
train_date	2020 - 06 - 17
src_alpha2	tl
tgt_alpha2	en
prefer_old	False
long_pair	tgl - eng
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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