Opus-mt-ur-en Open-source Machine Translation Model - Achieve Accurate Urdu-to-English Translation for Free

Opus Mt Ur En

Developed by Helsinki-NLP

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

Machine Translation

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Urdu translation #SentencePiece preprocessing #Low-resource language support

Downloads 6,382

Release Time : 3/2/2022

Model Overview

This model is specifically designed to translate Urdu text into English, utilizing the transformer-align architecture and SentencePiece preprocessing technology.

Model Features

Based on transformer-align architecture

Utilizes the advanced transformer-align architecture to better handle Urdu-to-English translation tasks.

SentencePiece preprocessing

Employs standardization and SentencePiece (spm32k) technology for text preprocessing to improve translation quality.

Multilingual support

Specifically optimized for Urdu-to-English translation tasks.

Model Capabilities

Text translation from Urdu to English

Handling standardized text

Support for SentencePiece tokenization

Use Cases

Language translation

Urdu document translation

Automatically translate Urdu documents into English

Achieved a BLEU score of 23.2 on the Tatoeba test set

Cross-language communication

Assist Urdu speakers in written communication with English speakers

🚀 urd-eng Translation Model

This project focuses on Urdu to English translation, offering a reliable solution for language conversion between these two languages.

✨ Features

Translation Direction: Translates from Urdu to English.
Model Type: Utilizes the transformer-align model.
Pre - processing: Applies normalization and SentencePiece (spm32k, spm32k).

📦 Installation

No specific installation steps are provided in the original document.

📚 Documentation

General Information

Source Group: Urdu
Target Group: English
OPUS Readme: urd-eng

Model Details

Model: transformer-align
Source Language(s): urd
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.urd.eng	23.2	0.435

System Info

Property	Details
hf_name	urd - eng
source_languages	urd
target_languages	eng
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/urd-eng/README.md
original_repo	Tatoeba - Challenge
tags	['translation']
languages	['ur', 'en']
src_constituents	{'urd'}
tgt_constituents	{'eng'}
src_multilingual	False
tgt_multilingual	False
prepro	normalization + SentencePiece (spm32k, spm32k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/urd-eng/opus-2020-06-17.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/urd-eng/opus-2020-06-17.test.txt
src_alpha3	urd
tgt_alpha3	eng
short_pair	ur - en
chrF2_score	0.435
bleu	23.2
brevity_penalty	0.975
ref_len	12029.0
src_name	Urdu
tgt_name	English
train_date	2020 - 06 - 17
src_alpha2	ur
tgt_alpha2	en
prefer_old	False
long_pair	urd - 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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