
### eng-sem

* source group: English 
* target group: Semitic languages 
*  OPUS readme: [eng-sem](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-sem/README.md)

*  model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz heb mlt tir
* 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: [opus2m-2020-08-01.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sem/opus2m-2020-08-01.zip)
* test set translations: [opus2m-2020-08-01.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sem/opus2m-2020-08-01.test.txt)
* test set scores: [opus2m-2020-08-01.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sem/opus2m-2020-08-01.eval.txt)

## Benchmarks

| testset               | BLEU  | chr-F |
|-----------------------|-------|-------|
| Tatoeba-test.eng-amh.eng.amh 	| 11.2 	| 0.480 |
| Tatoeba-test.eng-ara.eng.ara 	| 12.7 	| 0.417 |
| Tatoeba-test.eng-heb.eng.heb 	| 33.8 	| 0.564 |
| Tatoeba-test.eng-mlt.eng.mlt 	| 18.7 	| 0.554 |
| Tatoeba-test.eng.multi 	| 23.5 	| 0.486 |
| Tatoeba-test.eng-tir.eng.tir 	| 2.7 	| 0.248 |


### System Info: 
- hf_name: eng-sem

- source_languages: eng

- target_languages: sem

- opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-sem/README.md

- original_repo: Tatoeba-Challenge

- tags: ['translation']

- languages: ['en', 'mt', 'ar', 'he', 'ti', 'am', 'sem']

- src_constituents: {'eng'}

- tgt_constituents: {'apc', 'mlt', 'arz', 'ara', 'heb', 'tir', 'arq', 'afb', 'amh', 'acm', 'ary'}

- src_multilingual: False

- tgt_multilingual: True

- prepro:  normalization + SentencePiece (spm32k,spm32k)

- url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sem/opus2m-2020-08-01.zip

- url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sem/opus2m-2020-08-01.test.txt

- src_alpha3: eng

- tgt_alpha3: sem

- short_pair: en-sem

- chrF2_score: 0.486

- bleu: 23.5

- brevity_penalty: 1.0

- ref_len: 59258.0

- src_name: English

- tgt_name: Semitic languages

- train_date: 2020-08-01

- src_alpha2: en

- tgt_alpha2: sem

- prefer_old: False

- long_pair: eng-sem

- helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

- transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

- port_machine: brutasse

- port_time: 2020-08-21-14:41
{"language": ["en", "mt", "ar", "he", "ti", "am", "sem"], "license": "apache-2.0", "tags": ["translation"]}
transformers pytorch tf marian text2text-generation translation en mt ar he ti am sem license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #mt #ar #he #ti #am #sem #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

### eng-sem


* source group: English
* target group: Semitic languages
* OPUS readme: eng-sem
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz heb mlt tir
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 11.2, chr-F: 0.480
testset: URL, BLEU: 12.7, chr-F: 0.417
testset: URL, BLEU: 33.8, chr-F: 0.564
testset: URL, BLEU: 18.7, chr-F: 0.554
testset: URL, BLEU: 23.5, chr-F: 0.486
testset: URL, BLEU: 2.7, chr-F: 0.248


### System Info:


* hf\_name: eng-sem
* source\_languages: eng
* target\_languages: sem
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'mt', 'ar', 'he', 'ti', 'am', 'sem']
* src\_constituents: {'eng'}
* tgt\_constituents: {'apc', 'mlt', 'arz', 'ara', 'heb', 'tir', 'arq', 'afb', 'amh', 'acm', 'ary'}
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: sem
* short\_pair: en-sem
* chrF2\_score: 0.486
* bleu: 23.5
* brevity\_penalty: 1.0
* ref\_len: 59258.0
* src\_name: English
* tgt\_name: Semitic languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: sem
* prefer\_old: False
* long\_pair: eng-sem
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41



### eng-sem


* source group: English
* target group: Semitic languages
* OPUS readme: eng-sem
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz heb mlt tir
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 11.2, chr-F: 0.480
testset: URL, BLEU: 12.7, chr-F: 0.417
testset: URL, BLEU: 33.8, chr-F: 0.564
testset: URL, BLEU: 18.7, chr-F: 0.554
testset: URL, BLEU: 23.5, chr-F: 0.486
testset: URL, BLEU: 2.7, chr-F: 0.248 ### System Info:


* hf\_name: eng-sem
* source\_languages: eng
* target\_languages: sem
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'mt', 'ar', 'he', 'ti', 'am', 'sem']
* src\_constituents: {'eng'}
* tgt\_constituents: {'apc', 'mlt', 'arz', 'ara', 'heb', 'tir', 'arq', 'afb', 'amh', 'acm', 'ary'}
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: sem
* short\_pair: en-sem
* chrF2\_score: 0.486
* bleu: 23.5
* brevity\_penalty: 1.0
* ref\_len: 59258.0
* src\_name: English
* tgt\_name: Semitic languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: sem
* prefer\_old: False
* long\_pair: eng-sem
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41
TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #mt #ar #he #ti #am #sem #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### eng-sem


* source group: English
* target group: Semitic languages
* OPUS readme: eng-sem
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz heb mlt tir
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 11.2, chr-F: 0.480
testset: URL, BLEU: 12.7, chr-F: 0.417
testset: URL, BLEU: 33.8, chr-F: 0.564
testset: URL, BLEU: 18.7, chr-F: 0.554
testset: URL, BLEU: 23.5, chr-F: 0.486
testset: URL, BLEU: 2.7, chr-F: 0.248 ### System Info:


* hf\_name: eng-sem
* source\_languages: eng
* target\_languages: sem
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'mt', 'ar', 'he', 'ti', 'am', 'sem']
* src\_constituents: {'eng'}
* tgt\_constituents: {'apc', 'mlt', 'arz', 'ara', 'heb', 'tir', 'arq', 'afb', 'amh', 'acm', 'ary'}
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: sem
* short\_pair: en-sem
* chrF2\_score: 0.486
* bleu: 23.5
* brevity\_penalty: 1.0
* ref\_len: 59258.0
* src\_name: English
* tgt\_name: Semitic languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: sem
* prefer\_old: False
* long\_pair: eng-sem
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41
passage: TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #mt #ar #he #ti #am #sem #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
### eng-sem


* source group: English
* target group: Semitic languages
* OPUS readme: eng-sem
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz heb mlt tir
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 11.2, chr-F: 0.480
testset: URL, BLEU: 12.7, chr-F: 0.417
testset: URL, BLEU: 33.8, chr-F: 0.564
testset: URL, BLEU: 18.7, chr-F: 0.554
testset: URL, BLEU: 23.5, chr-F: 0.486
testset: URL, BLEU: 2.7, chr-F: 0.248