sem-sem
source group: Semitic languages
target group: Semitic languages
OPUS readme: sem-sem
model: transformer
source language(s): apc ara arq arz heb mlt
target language(s): apc ara arq arz heb mlt
model: transformer
pre-processing: normalization + SentencePiece (spm32k,spm32k)
a sentence initial language token is required in the form of
>>id<<
(id = valid target language ID)download original weights: opus-2020-07-27.zip
test set translations: opus-2020-07-27.test.txt
test set scores: opus-2020-07-27.eval.txt
Benchmarks
testset | BLEU | chr-F |
---|---|---|
Tatoeba-test.ara-ara.ara.ara | 4.2 | 0.200 |
Tatoeba-test.ara-heb.ara.heb | 34.0 | 0.542 |
Tatoeba-test.ara-mlt.ara.mlt | 16.6 | 0.513 |
Tatoeba-test.heb-ara.heb.ara | 18.8 | 0.477 |
Tatoeba-test.mlt-ara.mlt.ara | 20.7 | 0.388 |
Tatoeba-test.multi.multi | 27.1 | 0.507 |
System Info:
hf_name: sem-sem
source_languages: sem
target_languages: sem
opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/sem-sem/README.md
original_repo: Tatoeba-Challenge
tags: ['translation']
languages: ['mt', 'ar', 'he', 'ti', 'am', 'sem']
src_constituents: {'apc', 'mlt', 'arz', 'ara', 'heb', 'tir', 'arq', 'afb', 'amh', 'acm', 'ary'}
tgt_constituents: {'apc', 'mlt', 'arz', 'ara', 'heb', 'tir', 'arq', 'afb', 'amh', 'acm', 'ary'}
src_multilingual: True
tgt_multilingual: True
prepro: normalization + SentencePiece (spm32k,spm32k)
url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/sem-sem/opus-2020-07-27.zip
url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/sem-sem/opus-2020-07-27.test.txt
src_alpha3: sem
tgt_alpha3: sem
short_pair: sem-sem
chrF2_score: 0.507
bleu: 27.1
brevity_penalty: 0.972
ref_len: 13472.0
src_name: Semitic languages
tgt_name: Semitic languages
train_date: 2020-07-27
src_alpha2: sem
tgt_alpha2: sem
prefer_old: False
long_pair: sem-sem
helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine: brutasse
port_time: 2020-08-21-14:41
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