
### afa-eng

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

*  model: transformer
* source language(s): acm afb amh apc ara arq ary arz hau_Latn heb kab mlt rif_Latn shy_Latn som tir
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: [opus2m-2020-07-31.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.zip)
* test set translations: [opus2m-2020-07-31.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.test.txt)
* test set scores: [opus2m-2020-07-31.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.eval.txt)

## Benchmarks

| testset               | BLEU  | chr-F |
|-----------------------|-------|-------|
| Tatoeba-test.amh-eng.amh.eng 	| 35.9 	| 0.550 |
| Tatoeba-test.ara-eng.ara.eng 	| 36.6 	| 0.543 |
| Tatoeba-test.hau-eng.hau.eng 	| 11.9 	| 0.327 |
| Tatoeba-test.heb-eng.heb.eng 	| 42.7 	| 0.591 |
| Tatoeba-test.kab-eng.kab.eng 	| 4.3 	| 0.213 |
| Tatoeba-test.mlt-eng.mlt.eng 	| 44.3 	| 0.618 |
| Tatoeba-test.multi.eng 	| 27.1 	| 0.464 |
| Tatoeba-test.rif-eng.rif.eng 	| 3.5 	| 0.141 |
| Tatoeba-test.shy-eng.shy.eng 	| 0.6 	| 0.125 |
| Tatoeba-test.som-eng.som.eng 	| 23.6 	| 0.472 |
| Tatoeba-test.tir-eng.tir.eng 	| 13.1 	| 0.328 |


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

- source_languages: afa

- target_languages: eng

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

- original_repo: Tatoeba-Challenge

- tags: ['translation']

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

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

- tgt_constituents: {'eng'}

- src_multilingual: True

- tgt_multilingual: False

- prepro:  normalization + SentencePiece (spm32k,spm32k)

- url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.zip

- url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.test.txt

- src_alpha3: afa

- tgt_alpha3: eng

- short_pair: afa-en

- chrF2_score: 0.46399999999999997

- bleu: 27.1

- brevity_penalty: 1.0

- ref_len: 69373.0

- src_name: Afro-Asiatic languages

- tgt_name: English

- train_date: 2020-07-31

- src_alpha2: afa

- tgt_alpha2: en

- prefer_old: False

- long_pair: afa-eng

- helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

- transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

- port_machine: brutasse

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

### afa-eng


* source group: Afro-Asiatic languages
* target group: English
* OPUS readme: afa-eng
* model: transformer
* source language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som tir
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 35.9, chr-F: 0.550
testset: URL, BLEU: 36.6, chr-F: 0.543
testset: URL, BLEU: 11.9, chr-F: 0.327
testset: URL, BLEU: 42.7, chr-F: 0.591
testset: URL, BLEU: 4.3, chr-F: 0.213
testset: URL, BLEU: 44.3, chr-F: 0.618
testset: URL, BLEU: 27.1, chr-F: 0.464
testset: URL, BLEU: 3.5, chr-F: 0.141
testset: URL, BLEU: 0.6, chr-F: 0.125
testset: URL, BLEU: 23.6, chr-F: 0.472
testset: URL, BLEU: 13.1, chr-F: 0.328


### System Info:


* hf\_name: afa-eng
* source\_languages: afa
* target\_languages: eng
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['so', 'ti', 'am', 'he', 'mt', 'ar', 'afa', 'en']
* src\_constituents: {'som', 'rif\_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy\_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau\_Latn', 'acm', 'ary'}
* tgt\_constituents: {'eng'}
* src\_multilingual: True
* tgt\_multilingual: False
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: afa
* tgt\_alpha3: eng
* short\_pair: afa-en
* chrF2\_score: 0.46399999999999997
* bleu: 27.1
* brevity\_penalty: 1.0
* ref\_len: 69373.0
* src\_name: Afro-Asiatic languages
* tgt\_name: English
* train\_date: 2020-07-31
* src\_alpha2: afa
* tgt\_alpha2: en
* prefer\_old: False
* long\_pair: afa-eng
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41



### afa-eng


* source group: Afro-Asiatic languages
* target group: English
* OPUS readme: afa-eng
* model: transformer
* source language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som tir
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 35.9, chr-F: 0.550
testset: URL, BLEU: 36.6, chr-F: 0.543
testset: URL, BLEU: 11.9, chr-F: 0.327
testset: URL, BLEU: 42.7, chr-F: 0.591
testset: URL, BLEU: 4.3, chr-F: 0.213
testset: URL, BLEU: 44.3, chr-F: 0.618
testset: URL, BLEU: 27.1, chr-F: 0.464
testset: URL, BLEU: 3.5, chr-F: 0.141
testset: URL, BLEU: 0.6, chr-F: 0.125
testset: URL, BLEU: 23.6, chr-F: 0.472
testset: URL, BLEU: 13.1, chr-F: 0.328 ### System Info:


* hf\_name: afa-eng
* source\_languages: afa
* target\_languages: eng
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['so', 'ti', 'am', 'he', 'mt', 'ar', 'afa', 'en']
* src\_constituents: {'som', 'rif\_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy\_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau\_Latn', 'acm', 'ary'}
* tgt\_constituents: {'eng'}
* src\_multilingual: True
* tgt\_multilingual: False
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: afa
* tgt\_alpha3: eng
* short\_pair: afa-en
* chrF2\_score: 0.46399999999999997
* bleu: 27.1
* brevity\_penalty: 1.0
* ref\_len: 69373.0
* src\_name: Afro-Asiatic languages
* tgt\_name: English
* train\_date: 2020-07-31
* src\_alpha2: afa
* tgt\_alpha2: en
* prefer\_old: False
* long\_pair: afa-eng
* 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 #so #ti #am #he #mt #ar #afa #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### afa-eng


* source group: Afro-Asiatic languages
* target group: English
* OPUS readme: afa-eng
* model: transformer
* source language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som tir
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 35.9, chr-F: 0.550
testset: URL, BLEU: 36.6, chr-F: 0.543
testset: URL, BLEU: 11.9, chr-F: 0.327
testset: URL, BLEU: 42.7, chr-F: 0.591
testset: URL, BLEU: 4.3, chr-F: 0.213
testset: URL, BLEU: 44.3, chr-F: 0.618
testset: URL, BLEU: 27.1, chr-F: 0.464
testset: URL, BLEU: 3.5, chr-F: 0.141
testset: URL, BLEU: 0.6, chr-F: 0.125
testset: URL, BLEU: 23.6, chr-F: 0.472
testset: URL, BLEU: 13.1, chr-F: 0.328 ### System Info:


* hf\_name: afa-eng
* source\_languages: afa
* target\_languages: eng
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['so', 'ti', 'am', 'he', 'mt', 'ar', 'afa', 'en']
* src\_constituents: {'som', 'rif\_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy\_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau\_Latn', 'acm', 'ary'}
* tgt\_constituents: {'eng'}
* src\_multilingual: True
* tgt\_multilingual: False
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: afa
* tgt\_alpha3: eng
* short\_pair: afa-en
* chrF2\_score: 0.46399999999999997
* bleu: 27.1
* brevity\_penalty: 1.0
* ref\_len: 69373.0
* src\_name: Afro-Asiatic languages
* tgt\_name: English
* train\_date: 2020-07-31
* src\_alpha2: afa
* tgt\_alpha2: en
* prefer\_old: False
* long\_pair: afa-eng
* 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 #so #ti #am #he #mt #ar #afa #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
### afa-eng


* source group: Afro-Asiatic languages
* target group: English
* OPUS readme: afa-eng
* model: transformer
* source language(s): acm afb amh apc ara arq ary arz hau\_Latn heb kab mlt rif\_Latn shy\_Latn som tir
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 35.9, chr-F: 0.550
testset: URL, BLEU: 36.6, chr-F: 0.543
testset: URL, BLEU: 11.9, chr-F: 0.327
testset: URL, BLEU: 42.7, chr-F: 0.591
testset: URL, BLEU: 4.3, chr-F: 0.213
testset: URL, BLEU: 44.3, chr-F: 0.618
testset: URL, BLEU: 27.1, chr-F: 0.464
testset: URL, BLEU: 3.5, chr-F: 0.141
testset: URL, BLEU: 0.6, chr-F: 0.125
testset: URL, BLEU: 23.6, chr-F: 0.472
testset: URL, BLEU: 13.1, chr-F: 0.328