Opus-mt-ka-en Open-Source Machine Translation Model - Achieve Precise Georgian-to-English Translation for Free

Opus Mt Ka En

Developed by Helsinki-NLP

This is a Georgian-to-English 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 #Low-resource language translation #SentencePiece tokenization #Tatoeba benchmark

Downloads 962

Release Time : 3/2/2022

Model Overview

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

Model Features

Based on transformer-align architecture

Utilizes the advanced transformer-align architecture to optimize translation alignment.

Standardized preprocessing

Performs standardized preprocessing on input text to enhance translation quality.

SentencePiece tokenization

Uses spm12k tokenizer to process Georgian and English text.

Model Capabilities

Georgian to English text translation

Use Cases

Language translation

Daily phrase translation

Translates Georgian daily phrases into English.

Achieved a BLEU score of 37.9 on the Tatoeba test set

Simple text translation

Translates simple Georgian text into English.

Achieved a chr-F score of 0.538

🚀 kat-eng Translation Model

This is a translation model designed to translate from Georgian to English. It provides a reliable way for Georgian - English language conversion, with specific model details and performance benchmarks.

🚀 Quick Start

To start using this model, you can download the original weights from opus-2020-06-16.zip. You can also view the test set translations at opus-2020-06-16.test.txt and the test set scores at opus-2020-06-16.eval.txt.

✨ Features

Translation Direction: Translates from Georgian (source group) to English (target group).
Model Type: Uses the transformer-align model.
Pre - processing: Applies normalization and SentencePiece (spm12k, spm12k) techniques.

📚 Documentation

Model Information

Property	Details
Source Group	Georgian
Target Group	English
Model Type	transformer-align
Pre - processing	normalization + SentencePiece (spm12k,spm12k)
OPUS Readme	kat-eng
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

System Info

Property	Details
hf_name	kat-eng
source_languages	kat
target_languages	eng
opus_readme_url	https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/kat-eng/README.md
original_repo	Tatoeba-Challenge
tags	['translation']
languages	['ka', 'en']
src_constituents	{'kat'}
tgt_constituents	{'eng'}
src_multilingual	False
tgt_multilingual	False
prepro	normalization + SentencePiece (spm12k,spm12k)
url_model	https://object.pouta.csc.fi/Tatoeba-MT-models/kat-eng/opus-2020-06-16.zip
url_test_set	https://object.pouta.csc.fi/Tatoeba-MT-models/kat-eng/opus-2020-06-16.test.txt
src_alpha3	kat
tgt_alpha3	eng
short_pair	ka-en
chrF2_score	0.5379999999999999
bleu	37.9
brevity_penalty	0.991
ref_len	5992.0
src_name	Georgian
tgt_name	English
train_date	2020-06-16
src_alpha2	ka
tgt_alpha2	en
prefer_old	False
long_pair	kat-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.

🔧 Technical Details

Benchmarks

The model's performance on different test sets is as follows:

testset	BLEU	chr-F
Tatoeba-test.kat.eng	37.9	0.538

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