
### eng-afa

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

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

## Benchmarks

| testset               | BLEU  | chr-F |
|-----------------------|-------|-------|
| Tatoeba-test.eng-amh.eng.amh 	| 11.6 	| 0.504 |
| Tatoeba-test.eng-ara.eng.ara 	| 12.0 	| 0.404 |
| Tatoeba-test.eng-hau.eng.hau 	| 10.2 	| 0.429 |
| Tatoeba-test.eng-heb.eng.heb 	| 32.3 	| 0.551 |
| Tatoeba-test.eng-kab.eng.kab 	| 1.6 	| 0.191 |
| Tatoeba-test.eng-mlt.eng.mlt 	| 17.7 	| 0.551 |
| Tatoeba-test.eng.multi 	| 14.4 	| 0.375 |
| Tatoeba-test.eng-rif.eng.rif 	| 1.7 	| 0.103 |
| Tatoeba-test.eng-shy.eng.shy 	| 0.8 	| 0.090 |
| Tatoeba-test.eng-som.eng.som 	| 16.0 	| 0.429 |
| Tatoeba-test.eng-tir.eng.tir 	| 2.7 	| 0.238 |


### System Info: 
- hf_name: eng-afa

- source_languages: eng

- target_languages: afa

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

- original_repo: Tatoeba-Challenge

- tags: ['translation']

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

- src_constituents: {'eng'}

- tgt_constituents: {'som', 'rif_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau_Latn', 'acm', 'ary'}

- src_multilingual: False

- tgt_multilingual: True

- prepro:  normalization + SentencePiece (spm32k,spm32k)

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

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

- src_alpha3: eng

- tgt_alpha3: afa

- short_pair: en-afa

- chrF2_score: 0.375

- bleu: 14.4

- brevity_penalty: 1.0

- ref_len: 58110.0

- src_name: English

- tgt_name: Afro-Asiatic languages

- train_date: 2020-08-01

- src_alpha2: en

- tgt_alpha2: afa

- prefer_old: False

- long_pair: eng-afa

- helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

- transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

- port_machine: brutasse

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

### eng-afa


* source group: English
* target group: Afro-Asiatic languages
* OPUS readme: eng-afa
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som 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: 11.6, chr-F: 0.504
testset: URL, BLEU: 12.0, chr-F: 0.404
testset: URL, BLEU: 10.2, chr-F: 0.429
testset: URL, BLEU: 32.3, chr-F: 0.551
testset: URL, BLEU: 1.6, chr-F: 0.191
testset: URL, BLEU: 17.7, chr-F: 0.551
testset: URL, BLEU: 14.4, chr-F: 0.375
testset: URL, BLEU: 1.7, chr-F: 0.103
testset: URL, BLEU: 0.8, chr-F: 0.090
testset: URL, BLEU: 16.0, chr-F: 0.429
testset: URL, BLEU: 2.7, chr-F: 0.238


### System Info:


* hf\_name: eng-afa
* source\_languages: eng
* target\_languages: afa
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'so', 'ti', 'am', 'he', 'mt', 'ar', 'afa']
* src\_constituents: {'eng'}
* tgt\_constituents: {'som', 'rif\_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy\_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau\_Latn', '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: afa
* short\_pair: en-afa
* chrF2\_score: 0.375
* bleu: 14.4
* brevity\_penalty: 1.0
* ref\_len: 58110.0
* src\_name: English
* tgt\_name: Afro-Asiatic languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: afa
* prefer\_old: False
* long\_pair: eng-afa
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41



### eng-afa


* source group: English
* target group: Afro-Asiatic languages
* OPUS readme: eng-afa
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som 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: 11.6, chr-F: 0.504
testset: URL, BLEU: 12.0, chr-F: 0.404
testset: URL, BLEU: 10.2, chr-F: 0.429
testset: URL, BLEU: 32.3, chr-F: 0.551
testset: URL, BLEU: 1.6, chr-F: 0.191
testset: URL, BLEU: 17.7, chr-F: 0.551
testset: URL, BLEU: 14.4, chr-F: 0.375
testset: URL, BLEU: 1.7, chr-F: 0.103
testset: URL, BLEU: 0.8, chr-F: 0.090
testset: URL, BLEU: 16.0, chr-F: 0.429
testset: URL, BLEU: 2.7, chr-F: 0.238 ### System Info:


* hf\_name: eng-afa
* source\_languages: eng
* target\_languages: afa
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'so', 'ti', 'am', 'he', 'mt', 'ar', 'afa']
* src\_constituents: {'eng'}
* tgt\_constituents: {'som', 'rif\_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy\_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau\_Latn', '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: afa
* short\_pair: en-afa
* chrF2\_score: 0.375
* bleu: 14.4
* brevity\_penalty: 1.0
* ref\_len: 58110.0
* src\_name: English
* tgt\_name: Afro-Asiatic languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: afa
* prefer\_old: False
* long\_pair: eng-afa
* 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 #so #ti #am #he #mt #ar #afa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### eng-afa


* source group: English
* target group: Afro-Asiatic languages
* OPUS readme: eng-afa
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som 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: 11.6, chr-F: 0.504
testset: URL, BLEU: 12.0, chr-F: 0.404
testset: URL, BLEU: 10.2, chr-F: 0.429
testset: URL, BLEU: 32.3, chr-F: 0.551
testset: URL, BLEU: 1.6, chr-F: 0.191
testset: URL, BLEU: 17.7, chr-F: 0.551
testset: URL, BLEU: 14.4, chr-F: 0.375
testset: URL, BLEU: 1.7, chr-F: 0.103
testset: URL, BLEU: 0.8, chr-F: 0.090
testset: URL, BLEU: 16.0, chr-F: 0.429
testset: URL, BLEU: 2.7, chr-F: 0.238 ### System Info:


* hf\_name: eng-afa
* source\_languages: eng
* target\_languages: afa
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'so', 'ti', 'am', 'he', 'mt', 'ar', 'afa']
* src\_constituents: {'eng'}
* tgt\_constituents: {'som', 'rif\_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy\_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau\_Latn', '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: afa
* short\_pair: en-afa
* chrF2\_score: 0.375
* bleu: 14.4
* brevity\_penalty: 1.0
* ref\_len: 58110.0
* src\_name: English
* tgt\_name: Afro-Asiatic languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: afa
* prefer\_old: False
* long\_pair: eng-afa
* 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 #so #ti #am #he #mt #ar #afa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
### eng-afa


* source group: English
* target group: Afro-Asiatic languages
* OPUS readme: eng-afa
* model: transformer
* source language(s): eng
* target language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som 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: 11.6, chr-F: 0.504
testset: URL, BLEU: 12.0, chr-F: 0.404
testset: URL, BLEU: 10.2, chr-F: 0.429
testset: URL, BLEU: 32.3, chr-F: 0.551
testset: URL, BLEU: 1.6, chr-F: 0.191
testset: URL, BLEU: 17.7, chr-F: 0.551
testset: URL, BLEU: 14.4, chr-F: 0.375
testset: URL, BLEU: 1.7, chr-F: 0.103
testset: URL, BLEU: 0.8, chr-F: 0.090
testset: URL, BLEU: 16.0, chr-F: 0.429
testset: URL, BLEU: 2.7, chr-F: 0.238