
### eng-zlw

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

*  model: transformer
* source language(s): eng
* target language(s): ces csb_Latn dsb hsb pol
* 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-2020-08-02.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zlw/opus2m-2020-08-02.zip)
* test set translations: [opus2m-2020-08-02.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zlw/opus2m-2020-08-02.test.txt)
* test set scores: [opus2m-2020-08-02.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zlw/opus2m-2020-08-02.eval.txt)

## Benchmarks

| testset               | BLEU  | chr-F |
|-----------------------|-------|-------|
| newssyscomb2009-engces.eng.ces 	| 20.6 	| 0.488 |
| news-test2008-engces.eng.ces 	| 18.3 	| 0.466 |
| newstest2009-engces.eng.ces 	| 19.8 	| 0.483 |
| newstest2010-engces.eng.ces 	| 19.8 	| 0.486 |
| newstest2011-engces.eng.ces 	| 20.6 	| 0.489 |
| newstest2012-engces.eng.ces 	| 18.6 	| 0.464 |
| newstest2013-engces.eng.ces 	| 22.3 	| 0.495 |
| newstest2015-encs-engces.eng.ces 	| 21.7 	| 0.502 |
| newstest2016-encs-engces.eng.ces 	| 24.5 	| 0.521 |
| newstest2017-encs-engces.eng.ces 	| 20.1 	| 0.480 |
| newstest2018-encs-engces.eng.ces 	| 19.9 	| 0.483 |
| newstest2019-encs-engces.eng.ces 	| 21.2 	| 0.490 |
| Tatoeba-test.eng-ces.eng.ces 	| 43.7 	| 0.632 |
| Tatoeba-test.eng-csb.eng.csb 	| 1.2 	| 0.188 |
| Tatoeba-test.eng-dsb.eng.dsb 	| 1.5 	| 0.167 |
| Tatoeba-test.eng-hsb.eng.hsb 	| 5.7 	| 0.199 |
| Tatoeba-test.eng.multi 	| 42.8 	| 0.632 |
| Tatoeba-test.eng-pol.eng.pol 	| 43.2 	| 0.641 |


### System Info: 
- hf_name: eng-zlw

- source_languages: eng

- target_languages: zlw

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

- original_repo: Tatoeba-Challenge

- tags: ['translation']

- languages: ['en', 'pl', 'cs', 'zlw']

- src_constituents: {'eng'}

- tgt_constituents: {'csb_Latn', 'dsb', 'hsb', 'pol', 'ces'}

- src_multilingual: False

- tgt_multilingual: True

- prepro:  normalization + SentencePiece (spm32k,spm32k)

- url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zlw/opus2m-2020-08-02.zip

- url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-zlw/opus2m-2020-08-02.test.txt

- src_alpha3: eng

- tgt_alpha3: zlw

- short_pair: en-zlw

- chrF2_score: 0.632

- bleu: 42.8

- brevity_penalty: 0.973

- ref_len: 65397.0

- src_name: English

- tgt_name: West Slavic languages

- train_date: 2020-08-02

- src_alpha2: en

- tgt_alpha2: zlw

- prefer_old: False

- long_pair: eng-zlw

- helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

- transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

- port_machine: brutasse

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

### eng-zlw


* source group: English
* target group: West Slavic languages
* OPUS readme: eng-zlw
* model: transformer
* source language(s): eng
* target language(s): ces csb\_Latn dsb hsb pol
* 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: 20.6, chr-F: 0.488
testset: URL, BLEU: 18.3, chr-F: 0.466
testset: URL, BLEU: 19.8, chr-F: 0.483
testset: URL, BLEU: 19.8, chr-F: 0.486
testset: URL, BLEU: 20.6, chr-F: 0.489
testset: URL, BLEU: 18.6, chr-F: 0.464
testset: URL, BLEU: 22.3, chr-F: 0.495
testset: URL, BLEU: 21.7, chr-F: 0.502
testset: URL, BLEU: 24.5, chr-F: 0.521
testset: URL, BLEU: 20.1, chr-F: 0.480
testset: URL, BLEU: 19.9, chr-F: 0.483
testset: URL, BLEU: 21.2, chr-F: 0.490
testset: URL, BLEU: 43.7, chr-F: 0.632
testset: URL, BLEU: 1.2, chr-F: 0.188
testset: URL, BLEU: 1.5, chr-F: 0.167
testset: URL, BLEU: 5.7, chr-F: 0.199
testset: URL, BLEU: 42.8, chr-F: 0.632
testset: URL, BLEU: 43.2, chr-F: 0.641


### System Info:


* hf\_name: eng-zlw
* source\_languages: eng
* target\_languages: zlw
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'pl', 'cs', 'zlw']
* src\_constituents: {'eng'}
* tgt\_constituents: {'csb\_Latn', 'dsb', 'hsb', 'pol', 'ces'}
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: zlw
* short\_pair: en-zlw
* chrF2\_score: 0.632
* bleu: 42.8
* brevity\_penalty: 0.973
* ref\_len: 65397.0
* src\_name: English
* tgt\_name: West Slavic languages
* train\_date: 2020-08-02
* src\_alpha2: en
* tgt\_alpha2: zlw
* prefer\_old: False
* long\_pair: eng-zlw
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41



### eng-zlw


* source group: English
* target group: West Slavic languages
* OPUS readme: eng-zlw
* model: transformer
* source language(s): eng
* target language(s): ces csb\_Latn dsb hsb pol
* 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: 20.6, chr-F: 0.488
testset: URL, BLEU: 18.3, chr-F: 0.466
testset: URL, BLEU: 19.8, chr-F: 0.483
testset: URL, BLEU: 19.8, chr-F: 0.486
testset: URL, BLEU: 20.6, chr-F: 0.489
testset: URL, BLEU: 18.6, chr-F: 0.464
testset: URL, BLEU: 22.3, chr-F: 0.495
testset: URL, BLEU: 21.7, chr-F: 0.502
testset: URL, BLEU: 24.5, chr-F: 0.521
testset: URL, BLEU: 20.1, chr-F: 0.480
testset: URL, BLEU: 19.9, chr-F: 0.483
testset: URL, BLEU: 21.2, chr-F: 0.490
testset: URL, BLEU: 43.7, chr-F: 0.632
testset: URL, BLEU: 1.2, chr-F: 0.188
testset: URL, BLEU: 1.5, chr-F: 0.167
testset: URL, BLEU: 5.7, chr-F: 0.199
testset: URL, BLEU: 42.8, chr-F: 0.632
testset: URL, BLEU: 43.2, chr-F: 0.641 ### System Info:


* hf\_name: eng-zlw
* source\_languages: eng
* target\_languages: zlw
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'pl', 'cs', 'zlw']
* src\_constituents: {'eng'}
* tgt\_constituents: {'csb\_Latn', 'dsb', 'hsb', 'pol', 'ces'}
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: zlw
* short\_pair: en-zlw
* chrF2\_score: 0.632
* bleu: 42.8
* brevity\_penalty: 0.973
* ref\_len: 65397.0
* src\_name: English
* tgt\_name: West Slavic languages
* train\_date: 2020-08-02
* src\_alpha2: en
* tgt\_alpha2: zlw
* prefer\_old: False
* long\_pair: eng-zlw
* 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 #pl #cs #zlw #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### eng-zlw


* source group: English
* target group: West Slavic languages
* OPUS readme: eng-zlw
* model: transformer
* source language(s): eng
* target language(s): ces csb\_Latn dsb hsb pol
* 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: 20.6, chr-F: 0.488
testset: URL, BLEU: 18.3, chr-F: 0.466
testset: URL, BLEU: 19.8, chr-F: 0.483
testset: URL, BLEU: 19.8, chr-F: 0.486
testset: URL, BLEU: 20.6, chr-F: 0.489
testset: URL, BLEU: 18.6, chr-F: 0.464
testset: URL, BLEU: 22.3, chr-F: 0.495
testset: URL, BLEU: 21.7, chr-F: 0.502
testset: URL, BLEU: 24.5, chr-F: 0.521
testset: URL, BLEU: 20.1, chr-F: 0.480
testset: URL, BLEU: 19.9, chr-F: 0.483
testset: URL, BLEU: 21.2, chr-F: 0.490
testset: URL, BLEU: 43.7, chr-F: 0.632
testset: URL, BLEU: 1.2, chr-F: 0.188
testset: URL, BLEU: 1.5, chr-F: 0.167
testset: URL, BLEU: 5.7, chr-F: 0.199
testset: URL, BLEU: 42.8, chr-F: 0.632
testset: URL, BLEU: 43.2, chr-F: 0.641 ### System Info:


* hf\_name: eng-zlw
* source\_languages: eng
* target\_languages: zlw
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'pl', 'cs', 'zlw']
* src\_constituents: {'eng'}
* tgt\_constituents: {'csb\_Latn', 'dsb', 'hsb', 'pol', 'ces'}
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: zlw
* short\_pair: en-zlw
* chrF2\_score: 0.632
* bleu: 42.8
* brevity\_penalty: 0.973
* ref\_len: 65397.0
* src\_name: English
* tgt\_name: West Slavic languages
* train\_date: 2020-08-02
* src\_alpha2: en
* tgt\_alpha2: zlw
* prefer\_old: False
* long\_pair: eng-zlw
* 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 #pl #cs #zlw #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
