
### sla-eng

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

*  model: transformer
* source language(s): bel bel_Latn bos_Latn bul bul_Latn ces csb_Latn dsb hrv hsb mkd orv_Cyrl pol rue rus slv srp_Cyrl srp_Latn ukr
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: [opus2m-2020-08-01.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus2m-2020-08-01.zip)
* test set translations: [opus2m-2020-08-01.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus2m-2020-08-01.test.txt)
* test set scores: [opus2m-2020-08-01.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus2m-2020-08-01.eval.txt)

## Benchmarks

| testset               | BLEU  | chr-F |
|-----------------------|-------|-------|
| newssyscomb2009-ceseng.ces.eng 	| 26.7 	| 0.542 |
| newstest2009-ceseng.ces.eng 	| 25.2 	| 0.534 |
| newstest2010-ceseng.ces.eng 	| 25.9 	| 0.545 |
| newstest2011-ceseng.ces.eng 	| 26.8 	| 0.544 |
| newstest2012-ceseng.ces.eng 	| 25.6 	| 0.536 |
| newstest2012-ruseng.rus.eng 	| 32.5 	| 0.588 |
| newstest2013-ceseng.ces.eng 	| 28.8 	| 0.556 |
| newstest2013-ruseng.rus.eng 	| 26.4 	| 0.532 |
| newstest2014-csen-ceseng.ces.eng 	| 31.4 	| 0.591 |
| newstest2014-ruen-ruseng.rus.eng 	| 29.6 	| 0.576 |
| newstest2015-encs-ceseng.ces.eng 	| 28.2 	| 0.545 |
| newstest2015-enru-ruseng.rus.eng 	| 28.1 	| 0.551 |
| newstest2016-encs-ceseng.ces.eng 	| 30.0 	| 0.567 |
| newstest2016-enru-ruseng.rus.eng 	| 27.4 	| 0.548 |
| newstest2017-encs-ceseng.ces.eng 	| 26.5 	| 0.537 |
| newstest2017-enru-ruseng.rus.eng 	| 31.0 	| 0.574 |
| newstest2018-encs-ceseng.ces.eng 	| 27.9 	| 0.548 |
| newstest2018-enru-ruseng.rus.eng 	| 26.8 	| 0.545 |
| newstest2019-ruen-ruseng.rus.eng 	| 29.1 	| 0.562 |
| Tatoeba-test.bel-eng.bel.eng 	| 42.5 	| 0.609 |
| Tatoeba-test.bul-eng.bul.eng 	| 55.4 	| 0.697 |
| Tatoeba-test.ces-eng.ces.eng 	| 53.1 	| 0.688 |
| Tatoeba-test.csb-eng.csb.eng 	| 23.1 	| 0.446 |
| Tatoeba-test.dsb-eng.dsb.eng 	| 31.1 	| 0.467 |
| Tatoeba-test.hbs-eng.hbs.eng 	| 56.1 	| 0.702 |
| Tatoeba-test.hsb-eng.hsb.eng 	| 46.2 	| 0.597 |
| Tatoeba-test.mkd-eng.mkd.eng 	| 54.5 	| 0.680 |
| Tatoeba-test.multi.eng 	| 53.2 	| 0.683 |
| Tatoeba-test.orv-eng.orv.eng 	| 12.1 	| 0.292 |
| Tatoeba-test.pol-eng.pol.eng 	| 51.1 	| 0.671 |
| Tatoeba-test.rue-eng.rue.eng 	| 19.6 	| 0.389 |
| Tatoeba-test.rus-eng.rus.eng 	| 54.1 	| 0.686 |
| Tatoeba-test.slv-eng.slv.eng 	| 43.4 	| 0.610 |
| Tatoeba-test.ukr-eng.ukr.eng 	| 53.8 	| 0.685 |


### System Info: 
- hf_name: sla-eng

- source_languages: sla

- target_languages: eng

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

- original_repo: Tatoeba-Challenge

- tags: ['translation']

- languages: ['be', 'hr', 'mk', 'cs', 'ru', 'pl', 'bg', 'uk', 'sl', 'sla', 'en']

- src_constituents: {'bel', 'hrv', 'orv_Cyrl', 'mkd', 'bel_Latn', 'srp_Latn', 'bul_Latn', 'ces', 'bos_Latn', 'csb_Latn', 'dsb', 'hsb', 'rus', 'srp_Cyrl', 'pol', 'rue', 'bul', 'ukr', 'slv'}

- tgt_constituents: {'eng'}

- src_multilingual: True

- tgt_multilingual: False

- prepro:  normalization + SentencePiece (spm32k,spm32k)

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

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

- src_alpha3: sla

- tgt_alpha3: eng

- short_pair: sla-en

- chrF2_score: 0.6829999999999999

- bleu: 53.2

- brevity_penalty: 0.9740000000000001

- ref_len: 70897.0

- src_name: Slavic languages

- tgt_name: English

- train_date: 2020-08-01

- src_alpha2: sla

- tgt_alpha2: en

- prefer_old: False

- long_pair: sla-eng

- helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

- transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

- port_machine: brutasse

- port_time: 2020-08-21-14:41
{"language": ["be", "hr", "mk", "cs", "ru", "pl", "bg", "uk", "sl", "sla", "en"], "license": "apache-2.0", "tags": ["translation"]}
transformers pytorch tf marian text2text-generation translation be hr mk cs ru pl bg uk sl sla en license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #be #hr #mk #cs #ru #pl #bg #uk #sl #sla #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

### sla-eng


* source group: Slavic languages
* target group: English
* OPUS readme: sla-eng
* model: transformer
* source language(s): bel bel\_Latn bos\_Latn bul bul\_Latn ces csb\_Latn dsb hrv hsb mkd orv\_Cyrl pol rue rus slv srp\_Cyrl srp\_Latn ukr
* 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: 26.7, chr-F: 0.542
testset: URL, BLEU: 25.2, chr-F: 0.534
testset: URL, BLEU: 25.9, chr-F: 0.545
testset: URL, BLEU: 26.8, chr-F: 0.544
testset: URL, BLEU: 25.6, chr-F: 0.536
testset: URL, BLEU: 32.5, chr-F: 0.588
testset: URL, BLEU: 28.8, chr-F: 0.556
testset: URL, BLEU: 26.4, chr-F: 0.532
testset: URL, BLEU: 31.4, chr-F: 0.591
testset: URL, BLEU: 29.6, chr-F: 0.576
testset: URL, BLEU: 28.2, chr-F: 0.545
testset: URL, BLEU: 28.1, chr-F: 0.551
testset: URL, BLEU: 30.0, chr-F: 0.567
testset: URL, BLEU: 27.4, chr-F: 0.548
testset: URL, BLEU: 26.5, chr-F: 0.537
testset: URL, BLEU: 31.0, chr-F: 0.574
testset: URL, BLEU: 27.9, chr-F: 0.548
testset: URL, BLEU: 26.8, chr-F: 0.545
testset: URL, BLEU: 29.1, chr-F: 0.562
testset: URL, BLEU: 42.5, chr-F: 0.609
testset: URL, BLEU: 55.4, chr-F: 0.697
testset: URL, BLEU: 53.1, chr-F: 0.688
testset: URL, BLEU: 23.1, chr-F: 0.446
testset: URL, BLEU: 31.1, chr-F: 0.467
testset: URL, BLEU: 56.1, chr-F: 0.702
testset: URL, BLEU: 46.2, chr-F: 0.597
testset: URL, BLEU: 54.5, chr-F: 0.680
testset: URL, BLEU: 53.2, chr-F: 0.683
testset: URL, BLEU: 12.1, chr-F: 0.292
testset: URL, BLEU: 51.1, chr-F: 0.671
testset: URL, BLEU: 19.6, chr-F: 0.389
testset: URL, BLEU: 54.1, chr-F: 0.686
testset: URL, BLEU: 43.4, chr-F: 0.610
testset: URL, BLEU: 53.8, chr-F: 0.685


### System Info:


* hf\_name: sla-eng
* source\_languages: sla
* target\_languages: eng
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['be', 'hr', 'mk', 'cs', 'ru', 'pl', 'bg', 'uk', 'sl', 'sla', 'en']
* src\_constituents: {'bel', 'hrv', 'orv\_Cyrl', 'mkd', 'bel\_Latn', 'srp\_Latn', 'bul\_Latn', 'ces', 'bos\_Latn', 'csb\_Latn', 'dsb', 'hsb', 'rus', 'srp\_Cyrl', 'pol', 'rue', 'bul', 'ukr', 'slv'}
* tgt\_constituents: {'eng'}
* src\_multilingual: True
* tgt\_multilingual: False
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: sla
* tgt\_alpha3: eng
* short\_pair: sla-en
* chrF2\_score: 0.6829999999999999
* bleu: 53.2
* brevity\_penalty: 0.9740000000000001
* ref\_len: 70897.0
* src\_name: Slavic languages
* tgt\_name: English
* train\_date: 2020-08-01
* src\_alpha2: sla
* tgt\_alpha2: en
* prefer\_old: False
* long\_pair: sla-eng
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41



### sla-eng


* source group: Slavic languages
* target group: English
* OPUS readme: sla-eng
* model: transformer
* source language(s): bel bel\_Latn bos\_Latn bul bul\_Latn ces csb\_Latn dsb hrv hsb mkd orv\_Cyrl pol rue rus slv srp\_Cyrl srp\_Latn ukr
* 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: 26.7, chr-F: 0.542
testset: URL, BLEU: 25.2, chr-F: 0.534
testset: URL, BLEU: 25.9, chr-F: 0.545
testset: URL, BLEU: 26.8, chr-F: 0.544
testset: URL, BLEU: 25.6, chr-F: 0.536
testset: URL, BLEU: 32.5, chr-F: 0.588
testset: URL, BLEU: 28.8, chr-F: 0.556
testset: URL, BLEU: 26.4, chr-F: 0.532
testset: URL, BLEU: 31.4, chr-F: 0.591
testset: URL, BLEU: 29.6, chr-F: 0.576
testset: URL, BLEU: 28.2, chr-F: 0.545
testset: URL, BLEU: 28.1, chr-F: 0.551
testset: URL, BLEU: 30.0, chr-F: 0.567
testset: URL, BLEU: 27.4, chr-F: 0.548
testset: URL, BLEU: 26.5, chr-F: 0.537
testset: URL, BLEU: 31.0, chr-F: 0.574
testset: URL, BLEU: 27.9, chr-F: 0.548
testset: URL, BLEU: 26.8, chr-F: 0.545
testset: URL, BLEU: 29.1, chr-F: 0.562
testset: URL, BLEU: 42.5, chr-F: 0.609
testset: URL, BLEU: 55.4, chr-F: 0.697
testset: URL, BLEU: 53.1, chr-F: 0.688
testset: URL, BLEU: 23.1, chr-F: 0.446
testset: URL, BLEU: 31.1, chr-F: 0.467
testset: URL, BLEU: 56.1, chr-F: 0.702
testset: URL, BLEU: 46.2, chr-F: 0.597
testset: URL, BLEU: 54.5, chr-F: 0.680
testset: URL, BLEU: 53.2, chr-F: 0.683
testset: URL, BLEU: 12.1, chr-F: 0.292
testset: URL, BLEU: 51.1, chr-F: 0.671
testset: URL, BLEU: 19.6, chr-F: 0.389
testset: URL, BLEU: 54.1, chr-F: 0.686
testset: URL, BLEU: 43.4, chr-F: 0.610
testset: URL, BLEU: 53.8, chr-F: 0.685 ### System Info:


* hf\_name: sla-eng
* source\_languages: sla
* target\_languages: eng
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['be', 'hr', 'mk', 'cs', 'ru', 'pl', 'bg', 'uk', 'sl', 'sla', 'en']
* src\_constituents: {'bel', 'hrv', 'orv\_Cyrl', 'mkd', 'bel\_Latn', 'srp\_Latn', 'bul\_Latn', 'ces', 'bos\_Latn', 'csb\_Latn', 'dsb', 'hsb', 'rus', 'srp\_Cyrl', 'pol', 'rue', 'bul', 'ukr', 'slv'}
* tgt\_constituents: {'eng'}
* src\_multilingual: True
* tgt\_multilingual: False
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: sla
* tgt\_alpha3: eng
* short\_pair: sla-en
* chrF2\_score: 0.6829999999999999
* bleu: 53.2
* brevity\_penalty: 0.9740000000000001
* ref\_len: 70897.0
* src\_name: Slavic languages
* tgt\_name: English
* train\_date: 2020-08-01
* src\_alpha2: sla
* tgt\_alpha2: en
* prefer\_old: False
* long\_pair: sla-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 #be #hr #mk #cs #ru #pl #bg #uk #sl #sla #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### sla-eng


* source group: Slavic languages
* target group: English
* OPUS readme: sla-eng
* model: transformer
* source language(s): bel bel\_Latn bos\_Latn bul bul\_Latn ces csb\_Latn dsb hrv hsb mkd orv\_Cyrl pol rue rus slv srp\_Cyrl srp\_Latn ukr
* 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: 26.7, chr-F: 0.542
testset: URL, BLEU: 25.2, chr-F: 0.534
testset: URL, BLEU: 25.9, chr-F: 0.545
testset: URL, BLEU: 26.8, chr-F: 0.544
testset: URL, BLEU: 25.6, chr-F: 0.536
testset: URL, BLEU: 32.5, chr-F: 0.588
testset: URL, BLEU: 28.8, chr-F: 0.556
testset: URL, BLEU: 26.4, chr-F: 0.532
testset: URL, BLEU: 31.4, chr-F: 0.591
testset: URL, BLEU: 29.6, chr-F: 0.576
testset: URL, BLEU: 28.2, chr-F: 0.545
testset: URL, BLEU: 28.1, chr-F: 0.551
testset: URL, BLEU: 30.0, chr-F: 0.567
testset: URL, BLEU: 27.4, chr-F: 0.548
testset: URL, BLEU: 26.5, chr-F: 0.537
testset: URL, BLEU: 31.0, chr-F: 0.574
testset: URL, BLEU: 27.9, chr-F: 0.548
testset: URL, BLEU: 26.8, chr-F: 0.545
testset: URL, BLEU: 29.1, chr-F: 0.562
testset: URL, BLEU: 42.5, chr-F: 0.609
testset: URL, BLEU: 55.4, chr-F: 0.697
testset: URL, BLEU: 53.1, chr-F: 0.688
testset: URL, BLEU: 23.1, chr-F: 0.446
testset: URL, BLEU: 31.1, chr-F: 0.467
testset: URL, BLEU: 56.1, chr-F: 0.702
testset: URL, BLEU: 46.2, chr-F: 0.597
testset: URL, BLEU: 54.5, chr-F: 0.680
testset: URL, BLEU: 53.2, chr-F: 0.683
testset: URL, BLEU: 12.1, chr-F: 0.292
testset: URL, BLEU: 51.1, chr-F: 0.671
testset: URL, BLEU: 19.6, chr-F: 0.389
testset: URL, BLEU: 54.1, chr-F: 0.686
testset: URL, BLEU: 43.4, chr-F: 0.610
testset: URL, BLEU: 53.8, chr-F: 0.685 ### System Info:


* hf\_name: sla-eng
* source\_languages: sla
* target\_languages: eng
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['be', 'hr', 'mk', 'cs', 'ru', 'pl', 'bg', 'uk', 'sl', 'sla', 'en']
* src\_constituents: {'bel', 'hrv', 'orv\_Cyrl', 'mkd', 'bel\_Latn', 'srp\_Latn', 'bul\_Latn', 'ces', 'bos\_Latn', 'csb\_Latn', 'dsb', 'hsb', 'rus', 'srp\_Cyrl', 'pol', 'rue', 'bul', 'ukr', 'slv'}
* tgt\_constituents: {'eng'}
* src\_multilingual: True
* tgt\_multilingual: False
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: sla
* tgt\_alpha3: eng
* short\_pair: sla-en
* chrF2\_score: 0.6829999999999999
* bleu: 53.2
* brevity\_penalty: 0.9740000000000001
* ref\_len: 70897.0
* src\_name: Slavic languages
* tgt\_name: English
* train\_date: 2020-08-01
* src\_alpha2: sla
* tgt\_alpha2: en
* prefer\_old: False
* long\_pair: sla-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 #be #hr #mk #cs #ru #pl #bg #uk #sl #sla #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 passage: ### sla-eng


* source group: Slavic languages
* target group: English
* OPUS readme: sla-eng
* model: transformer
* source language(s): bel bel\_Latn bos\_Latn bul bul\_Latn ces csb\_Latn dsb hrv hsb mkd orv\_Cyrl pol rue rus slv srp\_Cyrl srp\_Latn ukr
* 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: 26.7, chr-F: 0.542
testset: URL, BLEU: 25.2, chr-F: 0.534
testset: URL, BLEU: 25.9, chr-F: 0.545
testset: URL, BLEU: 26.8, chr-F: 0.544
testset: URL, BLEU: 25.6, chr-F: 0.536
testset: URL, BLEU: 32.5, chr-F: 0.588
testset: URL, BLEU: 28.8, chr-F: 0.556
testset: URL, BLEU: 26.4, chr-F: 0.532
testset: URL, BLEU: 31.4, chr-F: 0.591
testset: URL, BLEU: 29.6, chr-F: 0.576
testset: URL, BLEU: 28.2, chr-F: 0.545
testset: URL, BLEU: 28.1, chr-F: 0.551
testset: URL, BLEU: 30.0, chr-F: 0.567
testset: URL, BLEU: 27.4, chr-F: 0.548
testset: URL, BLEU: 26.5, chr-F: 0.537
testset: URL, BLEU: 31.0, chr-F: 0.574
testset: URL, BLEU: 27.9, chr-F: 0.548
testset: URL, BLEU: 26.8, chr-F: 0.545
testset: URL, BLEU: 29.1, chr-F: 0.562
testset: URL, BLEU: 42.5, chr-F: 0.609
testset: URL, BLEU: 55.4, chr-F: 0.697
testset: URL, BLEU: 53.1, chr-F: 0.688
testset: URL, BLEU: 23.1, chr-F: 0.446
testset: URL, BLEU: 31.1, chr-F: 0.467
testset: URL, BLEU: 56.1, chr-F: 0.702
testset: URL, BLEU: 46.2, chr-F: 0.597
testset: URL, BLEU: 54.5, chr-F: 0.680
testset: URL, BLEU: 53.2, chr-F: 0.683
testset: URL, BLEU: 12.1, chr-F: 0.292
testset: URL, BLEU: 51.1, chr-F: 0.671
testset: URL, BLEU: 19.6, chr-F: 0.389
testset: URL, BLEU: 54.1, chr-F: 0.686
testset: URL, BLEU: 43.4, chr-F: 0.610
testset: URL, BLEU: 53.8, chr-F: 0.685