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--- |
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language: |
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- af |
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- de |
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- en |
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- fy |
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- gos |
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- lb |
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- nds |
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- nl |
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tags: |
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- translation |
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- opus-mt-tc |
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license: cc-by-4.0 |
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model-index: |
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- name: opus-mt-tc-big-gmw-gmw |
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results: |
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- task: |
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name: Translation afr-deu |
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type: translation |
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args: afr-deu |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: afr deu devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
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value: 30.2 |
|
- name: chr-F |
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type: chrf |
|
value: 0.58718 |
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- task: |
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name: Translation afr-eng |
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type: translation |
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args: afr-eng |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: afr eng devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
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value: 55.1 |
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- name: chr-F |
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type: chrf |
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value: 0.74826 |
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- task: |
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name: Translation afr-ltz |
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type: translation |
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args: afr-ltz |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: afr ltz devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
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value: 15.7 |
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- name: chr-F |
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type: chrf |
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value: 0.46826 |
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- task: |
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name: Translation afr-nld |
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type: translation |
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args: afr-nld |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: afr nld devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
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value: 22.5 |
|
- name: chr-F |
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type: chrf |
|
value: 0.54441 |
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- task: |
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name: Translation deu-afr |
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type: translation |
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args: deu-afr |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: deu afr devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 26.4 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.57835 |
|
- task: |
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name: Translation deu-eng |
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type: translation |
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args: deu-eng |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: deu eng devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 41.8 |
|
- name: chr-F |
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type: chrf |
|
value: 0.66990 |
|
- task: |
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name: Translation deu-ltz |
|
type: translation |
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args: deu-ltz |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: deu ltz devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 20.3 |
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- name: chr-F |
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type: chrf |
|
value: 0.52554 |
|
- task: |
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name: Translation deu-nld |
|
type: translation |
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args: deu-nld |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: deu nld devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 24.2 |
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- name: chr-F |
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type: chrf |
|
value: 0.55710 |
|
- task: |
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name: Translation eng-afr |
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type: translation |
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args: eng-afr |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: eng afr devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 40.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.68429 |
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- task: |
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name: Translation eng-deu |
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type: translation |
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args: eng-deu |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: eng deu devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 38.5 |
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- name: chr-F |
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type: chrf |
|
value: 0.64888 |
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- task: |
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name: Translation eng-ltz |
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type: translation |
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args: eng-ltz |
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dataset: |
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name: flores101-devtest |
|
type: flores_101 |
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args: eng ltz devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
|
value: 18.4 |
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- name: chr-F |
|
type: chrf |
|
value: 0.49231 |
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- task: |
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name: Translation eng-nld |
|
type: translation |
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args: eng-nld |
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dataset: |
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name: flores101-devtest |
|
type: flores_101 |
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args: eng nld devtest |
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metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 26.8 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.57984 |
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- task: |
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name: Translation ltz-afr |
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type: translation |
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args: ltz-afr |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: ltz afr devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 23.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53623 |
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- task: |
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name: Translation ltz-deu |
|
type: translation |
|
args: ltz-deu |
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dataset: |
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name: flores101-devtest |
|
type: flores_101 |
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args: ltz deu devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
|
value: 30.0 |
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- name: chr-F |
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type: chrf |
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value: 0.59122 |
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- task: |
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name: Translation ltz-eng |
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type: translation |
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args: ltz-eng |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: ltz eng devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 31.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.57557 |
|
- task: |
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name: Translation ltz-nld |
|
type: translation |
|
args: ltz-nld |
|
dataset: |
|
name: flores101-devtest |
|
type: flores_101 |
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args: ltz nld devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
|
value: 18.6 |
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- name: chr-F |
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type: chrf |
|
value: 0.49312 |
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- task: |
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name: Translation nld-afr |
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type: translation |
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args: nld-afr |
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dataset: |
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name: flores101-devtest |
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type: flores_101 |
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args: nld afr devtest |
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metrics: |
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- name: BLEU |
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type: bleu |
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value: 20.0 |
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- name: chr-F |
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type: chrf |
|
value: 0.52409 |
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- task: |
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name: Translation nld-deu |
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type: translation |
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args: nld-deu |
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dataset: |
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name: flores101-devtest |
|
type: flores_101 |
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args: nld deu devtest |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 22.6 |
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- name: chr-F |
|
type: chrf |
|
value: 0.53898 |
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- task: |
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name: Translation nld-eng |
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type: translation |
|
args: nld-eng |
|
dataset: |
|
name: flores101-devtest |
|
type: flores_101 |
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args: nld eng devtest |
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metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 30.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.58970 |
|
- task: |
|
name: Translation nld-ltz |
|
type: translation |
|
args: nld-ltz |
|
dataset: |
|
name: flores101-devtest |
|
type: flores_101 |
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args: nld ltz devtest |
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metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 11.8 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.42637 |
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- task: |
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name: Translation deu-eng |
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type: translation |
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args: deu-eng |
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dataset: |
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name: multi30k_test_2016_flickr |
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type: multi30k-2016_flickr |
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args: deu-eng |
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metrics: |
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- name: BLEU |
|
type: bleu |
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value: 39.9 |
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- name: chr-F |
|
type: chrf |
|
value: 0.60928 |
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- task: |
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name: Translation eng-deu |
|
type: translation |
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args: eng-deu |
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dataset: |
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name: multi30k_test_2016_flickr |
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type: multi30k-2016_flickr |
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args: eng-deu |
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metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 35.4 |
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- name: chr-F |
|
type: chrf |
|
value: 0.64172 |
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- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: multi30k_test_2017_flickr |
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type: multi30k-2017_flickr |
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args: deu-eng |
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metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 40.5 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.63154 |
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- task: |
|
name: Translation eng-deu |
|
type: translation |
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args: eng-deu |
|
dataset: |
|
name: multi30k_test_2017_flickr |
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type: multi30k-2017_flickr |
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args: eng-deu |
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metrics: |
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- name: BLEU |
|
type: bleu |
|
value: 34.2 |
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- name: chr-F |
|
type: chrf |
|
value: 0.63078 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: multi30k_test_2017_mscoco |
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type: multi30k-2017_mscoco |
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args: deu-eng |
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metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 32.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.55708 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: multi30k_test_2017_mscoco |
|
type: multi30k-2017_mscoco |
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args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 29.1 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.57537 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: multi30k_test_2018_flickr |
|
type: multi30k-2018_flickr |
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args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 36.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59422 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: multi30k_test_2018_flickr |
|
type: multi30k-2018_flickr |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 30.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59597 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: news-test2008 |
|
type: news-test2008 |
|
args: deu-eng |
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metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 27.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.54601 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: news-test2008 |
|
type: news-test2008 |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 23.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53149 |
|
- task: |
|
name: Translation afr-deu |
|
type: translation |
|
args: afr-deu |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
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type: tatoeba_mt |
|
args: afr-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 50.4 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.68679 |
|
- task: |
|
name: Translation afr-eng |
|
type: translation |
|
args: afr-eng |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: afr-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 56.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.70682 |
|
- task: |
|
name: Translation afr-nld |
|
type: translation |
|
args: afr-nld |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: afr-nld |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 55.5 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.71516 |
|
- task: |
|
name: Translation deu-afr |
|
type: translation |
|
args: deu-afr |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: deu-afr |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 54.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.70274 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 48.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.66023 |
|
- task: |
|
name: Translation deu-nds |
|
type: translation |
|
args: deu-nds |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: deu-nds |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 23.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.48058 |
|
- task: |
|
name: Translation deu-nld |
|
type: translation |
|
args: deu-nld |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: deu-nld |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 54.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.71440 |
|
- task: |
|
name: Translation eng-afr |
|
type: translation |
|
args: eng-afr |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: eng-afr |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 56.5 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.71995 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 42.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.63103 |
|
- task: |
|
name: Translation eng-fry |
|
type: translation |
|
args: eng-fry |
|
dataset: |
|
name: tatoeba-test-v2021-03-30 |
|
type: tatoeba_mt |
|
args: eng-fry |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 21.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.38580 |
|
- task: |
|
name: Translation eng-nld |
|
type: translation |
|
args: eng-nld |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: eng-nld |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 54.5 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.71062 |
|
- task: |
|
name: Translation fry-eng |
|
type: translation |
|
args: fry-eng |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: fry-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 25.1 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.40545 |
|
- task: |
|
name: Translation fry-nld |
|
type: translation |
|
args: fry-nld |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: fry-nld |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 41.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.55771 |
|
- task: |
|
name: Translation gos-deu |
|
type: translation |
|
args: gos-deu |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: gos-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 25.4 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.45302 |
|
- task: |
|
name: Translation gos-eng |
|
type: translation |
|
args: gos-eng |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: gos-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 24.1 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.37628 |
|
- task: |
|
name: Translation gos-nld |
|
type: translation |
|
args: gos-nld |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: gos-nld |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 26.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.45777 |
|
- task: |
|
name: Translation ltz-deu |
|
type: translation |
|
args: ltz-deu |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: ltz-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 21.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.37165 |
|
- task: |
|
name: Translation ltz-eng |
|
type: translation |
|
args: ltz-eng |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: ltz-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 30.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.37784 |
|
- task: |
|
name: Translation ltz-nld |
|
type: translation |
|
args: ltz-nld |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: ltz-nld |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 26.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.32823 |
|
- task: |
|
name: Translation nds-deu |
|
type: translation |
|
args: nds-deu |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: nds-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 45.4 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.64008 |
|
- task: |
|
name: Translation nds-eng |
|
type: translation |
|
args: nds-eng |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: nds-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 38.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.55193 |
|
- task: |
|
name: Translation nds-nld |
|
type: translation |
|
args: nds-nld |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: nds-nld |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 50.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.66943 |
|
- task: |
|
name: Translation nld-afr |
|
type: translation |
|
args: nld-afr |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: nld-afr |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 62.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.76610 |
|
- task: |
|
name: Translation nld-deu |
|
type: translation |
|
args: nld-deu |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: nld-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 56.8 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.73162 |
|
- task: |
|
name: Translation nld-eng |
|
type: translation |
|
args: nld-eng |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: nld-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 60.5 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.74088 |
|
- task: |
|
name: Translation nld-fry |
|
type: translation |
|
args: nld-fry |
|
dataset: |
|
name: tatoeba-test-v2021-08-07 |
|
type: tatoeba_mt |
|
args: nld-fry |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 31.4 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.48460 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2009 |
|
type: wmt-2009-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 25.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53747 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2009 |
|
type: wmt-2009-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 22.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.53283 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2010 |
|
type: wmt-2010-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 30.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.58355 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2010 |
|
type: wmt-2010-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 25.8 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.54885 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2011 |
|
type: wmt-2011-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 26.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.54883 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2011 |
|
type: wmt-2011-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 23.1 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.52712 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2012 |
|
type: wmt-2012-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 28.5 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.56153 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2012 |
|
type: wmt-2012-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 23.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.52662 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2013 |
|
type: wmt-2013-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 31.4 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.57770 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2013 |
|
type: wmt-2013-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 27.8 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.55774 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2014 |
|
type: wmt-2014-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 33.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59826 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2014 |
|
type: wmt-2014-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 29.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59301 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2015 |
|
type: wmt-2015-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 33.4 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59660 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2015 |
|
type: wmt-2015-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 32.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59889 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2016 |
|
type: wmt-2016-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 39.8 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.64736 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2016 |
|
type: wmt-2016-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 38.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.64427 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2017 |
|
type: wmt-2017-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 35.2 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.60933 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2017 |
|
type: wmt-2017-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 30.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.59257 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2018 |
|
type: wmt-2018-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 42.6 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.66797 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2018 |
|
type: wmt-2018-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 46.5 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.69605 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2019 |
|
type: wmt-2019-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 39.7 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.63749 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2019 |
|
type: wmt-2019-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 42.9 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.66751 |
|
- task: |
|
name: Translation deu-eng |
|
type: translation |
|
args: deu-eng |
|
dataset: |
|
name: newstest2020 |
|
type: wmt-2020-news |
|
args: deu-eng |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 35.0 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.61200 |
|
- task: |
|
name: Translation eng-deu |
|
type: translation |
|
args: eng-deu |
|
dataset: |
|
name: newstest2020 |
|
type: wmt-2020-news |
|
args: eng-deu |
|
metrics: |
|
- name: BLEU |
|
type: bleu |
|
value: 32.3 |
|
- name: chr-F |
|
type: chrf |
|
value: 0.60411 |
|
--- |
|
# opus-mt-tc-big-gmw-gmw |
|
|
|
## Table of Contents |
|
- [Model Details](#model-details) |
|
- [Uses](#uses) |
|
- [Risks, Limitations and Biases](#risks-limitations-and-biases) |
|
- [How to Get Started With the Model](#how-to-get-started-with-the-model) |
|
- [Training](#training) |
|
- [Evaluation](#evaluation) |
|
- [Citation Information](#citation-information) |
|
- [Acknowledgements](#acknowledgements) |
|
|
|
## Model Details |
|
|
|
Neural machine translation model for translating from West Germanic languages (gmw) to West Germanic languages (gmw). |
|
|
|
This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train). |
|
**Model Description:** |
|
- **Developed by:** Language Technology Research Group at the University of Helsinki |
|
- **Model Type:** Translation (transformer-big) |
|
- **Release**: 2022-08-11 |
|
- **License:** CC-BY-4.0 |
|
- **Language(s):** |
|
- Source Language(s): afr deu eng enm fry gos gsw hrx ksh ltz nds nld pdc sco stq swg tpi yid |
|
- Target Language(s): afr ang deu eng enm fry gos ltz nds nld sco tpi yid |
|
- Language Pair(s): afr-deu afr-eng afr-nld deu-afr deu-eng deu-ltz deu-nds deu-nld eng-afr eng-deu eng-fry eng-nld fry-eng fry-nld gos-deu gos-eng gos-nld ltz-afr ltz-deu ltz-eng ltz-nld nds-deu nds-eng nds-nld nld-afr nld-deu nld-eng nld-fry |
|
- Valid Target Language Labels: >>act<< >>afr<< >>afs<< >>aig<< >>ang<< >>ang_Latn<< >>bah<< >>bar<< >>bis<< >>bjs<< >>brc<< >>bzj<< >>bzj_Latn<< >>bzk<< >>cim<< >>dcr<< >>deu<< >>djk<< >>djk_Latn<< >>drt<< >>drt_Latn<< >>dum<< >>eng<< >>enm<< >>enm_Latn<< >>fpe<< >>frk<< >>frr<< >>fry<< >>gcl<< >>gct<< >>geh<< >>gmh<< >>gml<< >>goh<< >>gos<< >>gpe<< >>gsw<< >>gul<< >>gyn<< >>hrx<< >>hrx_Latn<< >>hwc<< >>icr<< >>jam<< >>jvd<< >>kri<< >>ksh<< >>kww<< >>lim<< >>lng<< >>ltz<< >>mhn<< >>nds<< >>nld<< >>odt<< >>ofs<< >>ofs_Latn<< >>oor<< >>osx<< >>pcm<< >>pdc<< >>pdt<< >>pey<< >>pfl<< >>pih<< >>pih_Latn<< >>pis<< >>pis_Latn<< >>qlm<< >>rop<< >>sco<< >>sdz<< >>skw<< >>sli<< >>srm<< >>srm_Latn<< >>srn<< >>stl<< >>stq<< >>svc<< >>swg<< >>sxu<< >>tch<< >>tcs<< >>tgh<< >>tpi<< >>trf<< >>twd<< >>uln<< >>vel<< >>vic<< >>vls<< >>vmf<< >>wae<< >>wep<< >>wes<< >>wes_Latn<< >>wym<< >>ydd<< >>yec<< >>yid<< >>yih<< >>zea<< |
|
- **Original Model**: [opusTCv20210807_transformer-big_2022-08-11.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-gmw/opusTCv20210807_transformer-big_2022-08-11.zip) |
|
- **Resources for more information:** |
|
- [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) |
|
- More information about released models for this language pair: [OPUS-MT gmw-gmw README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmw-gmw/README.md) |
|
- [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian) |
|
- [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/ |
|
|
|
This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>afr<<` |
|
|
|
## Uses |
|
|
|
This model can be used for translation and text-to-text generation. |
|
|
|
## Risks, Limitations and Biases |
|
|
|
**CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.** |
|
|
|
Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). |
|
|
|
## How to Get Started With the Model |
|
|
|
A short example code: |
|
|
|
```python |
|
from transformers import MarianMTModel, MarianTokenizer |
|
|
|
src_text = [ |
|
">>nds<< Red keinen Quatsch.", |
|
">>eng<< Findet ihr das nicht etwas übereilt?" |
|
] |
|
|
|
model_name = "pytorch-models/opus-mt-tc-big-gmw-gmw" |
|
tokenizer = MarianTokenizer.from_pretrained(model_name) |
|
model = MarianMTModel.from_pretrained(model_name) |
|
translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True)) |
|
|
|
for t in translated: |
|
print( tokenizer.decode(t, skip_special_tokens=True) ) |
|
|
|
# expected output: |
|
# Kiek ok bi: Rott. |
|
# Aren't you in a hurry? |
|
``` |
|
|
|
You can also use OPUS-MT models with the transformers pipelines, for example: |
|
|
|
```python |
|
from transformers import pipeline |
|
pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-gmw-gmw") |
|
print(pipe(">>nds<< Red keinen Quatsch.")) |
|
|
|
# expected output: Kiek ok bi: Rott. |
|
``` |
|
|
|
## Training |
|
|
|
- **Data**: opusTCv20210807 ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge)) |
|
- **Pre-processing**: SentencePiece (spm32k,spm32k) |
|
- **Model Type:** transformer-big |
|
- **Original MarianNMT Model**: [opusTCv20210807_transformer-big_2022-08-11.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-gmw/opusTCv20210807_transformer-big_2022-08-11.zip) |
|
- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train) |
|
|
|
## Evaluation |
|
|
|
* test set translations: [opusTCv20210807_transformer-big_2022-08-11.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-gmw/opusTCv20210807_transformer-big_2022-08-11.test.txt) |
|
* test set scores: [opusTCv20210807_transformer-big_2022-08-11.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-gmw/opusTCv20210807_transformer-big_2022-08-11.eval.txt) |
|
* benchmark results: [benchmark_results.txt](benchmark_results.txt) |
|
* benchmark output: [benchmark_translations.zip](benchmark_translations.zip) |
|
|
|
| langpair | testset | chr-F | BLEU | #sent | #words | |
|
|----------|---------|-------|-------|-------|--------| |
|
| afr-deu | tatoeba-test-v2021-08-07 | 0.68679 | 50.4 | 1583 | 9105 | |
|
| afr-eng | tatoeba-test-v2021-08-07 | 0.70682 | 56.6 | 1374 | 9622 | |
|
| afr-nld | tatoeba-test-v2021-08-07 | 0.71516 | 55.5 | 1056 | 6710 | |
|
| deu-afr | tatoeba-test-v2021-08-07 | 0.70274 | 54.3 | 1583 | 9507 | |
|
| deu-eng | tatoeba-test-v2021-08-07 | 0.66023 | 48.6 | 17565 | 149462 | |
|
| deu-nds | tatoeba-test-v2021-08-07 | 0.48058 | 23.2 | 9999 | 76137 | |
|
| deu-nld | tatoeba-test-v2021-08-07 | 0.71440 | 54.6 | 10218 | 75235 | |
|
| deu-yid | tatoeba-test-v2021-08-07 | 9.211 | 0.4 | 853 | 5355 | |
|
| eng-afr | tatoeba-test-v2021-08-07 | 0.71995 | 56.5 | 1374 | 10317 | |
|
| eng-deu | tatoeba-test-v2021-08-07 | 0.63103 | 42.0 | 17565 | 151568 | |
|
| eng-nld | tatoeba-test-v2021-08-07 | 0.71062 | 54.5 | 12696 | 91796 | |
|
| eng-yid | tatoeba-test-v2021-08-07 | 9.624 | 0.4 | 2483 | 16395 | |
|
| fry-eng | tatoeba-test-v2021-08-07 | 0.40545 | 25.1 | 220 | 1573 | |
|
| fry-nld | tatoeba-test-v2021-08-07 | 0.55771 | 41.7 | 260 | 1854 | |
|
| gos-deu | tatoeba-test-v2021-08-07 | 0.45302 | 25.4 | 207 | 1168 | |
|
| gos-eng | tatoeba-test-v2021-08-07 | 0.37628 | 24.1 | 1154 | 5635 | |
|
| gos-nld | tatoeba-test-v2021-08-07 | 0.45777 | 26.2 | 1852 | 9903 | |
|
| ltz-deu | tatoeba-test-v2021-08-07 | 0.37165 | 21.3 | 347 | 2208 | |
|
| ltz-eng | tatoeba-test-v2021-08-07 | 0.37784 | 30.3 | 293 | 1840 | |
|
| ltz-nld | tatoeba-test-v2021-08-07 | 0.32823 | 26.7 | 292 | 1685 | |
|
| nds-deu | tatoeba-test-v2021-08-07 | 0.64008 | 45.4 | 9999 | 74564 | |
|
| nds-eng | tatoeba-test-v2021-08-07 | 0.55193 | 38.3 | 2500 | 17589 | |
|
| nds-nld | tatoeba-test-v2021-08-07 | 0.66943 | 50.0 | 1657 | 11490 | |
|
| nld-afr | tatoeba-test-v2021-08-07 | 0.76610 | 62.3 | 1056 | 6823 | |
|
| nld-deu | tatoeba-test-v2021-08-07 | 0.73162 | 56.8 | 10218 | 74131 | |
|
| nld-eng | tatoeba-test-v2021-08-07 | 0.74088 | 60.5 | 12696 | 89978 | |
|
| nld-fry | tatoeba-test-v2021-08-07 | 0.48460 | 31.4 | 260 | 1857 | |
|
| nld-nds | tatoeba-test-v2021-08-07 | 0.43779 | 19.9 | 1657 | 11711 | |
|
| swg-deu | tatoeba-test-v2021-08-07 | 0.40348 | 16.1 | 1523 | 15632 | |
|
| yid-deu | tatoeba-test-v2021-08-07 | 6.305 | 0.1 | 853 | 5173 | |
|
| yid-eng | tatoeba-test-v2021-08-07 | 3.704 | 0.1 | 2483 | 15452 | |
|
| afr-deu | flores101-devtest | 0.58718 | 30.2 | 1012 | 25094 | |
|
| afr-eng | flores101-devtest | 0.74826 | 55.1 | 1012 | 24721 | |
|
| afr-ltz | flores101-devtest | 0.46826 | 15.7 | 1012 | 25087 | |
|
| afr-nld | flores101-devtest | 0.54441 | 22.5 | 1012 | 25467 | |
|
| deu-afr | flores101-devtest | 0.57835 | 26.4 | 1012 | 25740 | |
|
| deu-eng | flores101-devtest | 0.66990 | 41.8 | 1012 | 24721 | |
|
| deu-ltz | flores101-devtest | 0.52554 | 20.3 | 1012 | 25087 | |
|
| deu-nld | flores101-devtest | 0.55710 | 24.2 | 1012 | 25467 | |
|
| eng-afr | flores101-devtest | 0.68429 | 40.7 | 1012 | 25740 | |
|
| eng-deu | flores101-devtest | 0.64888 | 38.5 | 1012 | 25094 | |
|
| eng-ltz | flores101-devtest | 0.49231 | 18.4 | 1012 | 25087 | |
|
| eng-nld | flores101-devtest | 0.57984 | 26.8 | 1012 | 25467 | |
|
| ltz-afr | flores101-devtest | 0.53623 | 23.2 | 1012 | 25740 | |
|
| ltz-deu | flores101-devtest | 0.59122 | 30.0 | 1012 | 25094 | |
|
| ltz-eng | flores101-devtest | 0.57557 | 31.0 | 1012 | 24721 | |
|
| ltz-nld | flores101-devtest | 0.49312 | 18.6 | 1012 | 25467 | |
|
| nld-afr | flores101-devtest | 0.52409 | 20.0 | 1012 | 25740 | |
|
| nld-deu | flores101-devtest | 0.53898 | 22.6 | 1012 | 25094 | |
|
| nld-eng | flores101-devtest | 0.58970 | 30.7 | 1012 | 24721 | |
|
| nld-ltz | flores101-devtest | 0.42637 | 11.8 | 1012 | 25087 | |
|
| deu-eng | multi30k_test_2016_flickr | 0.60928 | 39.9 | 1000 | 12955 | |
|
| eng-deu | multi30k_test_2016_flickr | 0.64172 | 35.4 | 1000 | 12106 | |
|
| deu-eng | multi30k_test_2017_flickr | 0.63154 | 40.5 | 1000 | 11374 | |
|
| eng-deu | multi30k_test_2017_flickr | 0.63078 | 34.2 | 1000 | 10755 | |
|
| deu-eng | multi30k_test_2017_mscoco | 0.55708 | 32.2 | 461 | 5231 | |
|
| eng-deu | multi30k_test_2017_mscoco | 0.57537 | 29.1 | 461 | 5158 | |
|
| deu-eng | multi30k_test_2018_flickr | 0.59422 | 36.9 | 1071 | 14689 | |
|
| eng-deu | multi30k_test_2018_flickr | 0.59597 | 30.0 | 1071 | 13703 | |
|
| deu-eng | newssyscomb2009 | 0.54993 | 28.2 | 502 | 11818 | |
|
| eng-deu | newssyscomb2009 | 0.53867 | 23.2 | 502 | 11271 | |
|
| deu-eng | news-test2008 | 0.54601 | 27.2 | 2051 | 49380 | |
|
| eng-deu | news-test2008 | 0.53149 | 23.6 | 2051 | 47447 | |
|
| deu-eng | newstest2009 | 0.53747 | 25.9 | 2525 | 65399 | |
|
| eng-deu | newstest2009 | 0.53283 | 22.9 | 2525 | 62816 | |
|
| deu-eng | newstest2010 | 0.58355 | 30.6 | 2489 | 61711 | |
|
| eng-deu | newstest2010 | 0.54885 | 25.8 | 2489 | 61503 | |
|
| deu-eng | newstest2011 | 0.54883 | 26.3 | 3003 | 74681 | |
|
| eng-deu | newstest2011 | 0.52712 | 23.1 | 3003 | 72981 | |
|
| deu-eng | newstest2012 | 0.56153 | 28.5 | 3003 | 72812 | |
|
| eng-deu | newstest2012 | 0.52662 | 23.3 | 3003 | 72886 | |
|
| deu-eng | newstest2013 | 0.57770 | 31.4 | 3000 | 64505 | |
|
| eng-deu | newstest2013 | 0.55774 | 27.8 | 3000 | 63737 | |
|
| deu-eng | newstest2014 | 0.59826 | 33.2 | 3003 | 67337 | |
|
| eng-deu | newstest2014 | 0.59301 | 29.0 | 3003 | 62688 | |
|
| deu-eng | newstest2015 | 0.59660 | 33.4 | 2169 | 46443 | |
|
| eng-deu | newstest2015 | 0.59889 | 32.3 | 2169 | 44260 | |
|
| deu-eng | newstest2016 | 0.64736 | 39.8 | 2999 | 64119 | |
|
| eng-deu | newstest2016 | 0.64427 | 38.3 | 2999 | 62669 | |
|
| deu-eng | newstest2017 | 0.60933 | 35.2 | 3004 | 64399 | |
|
| eng-deu | newstest2017 | 0.59257 | 30.7 | 3004 | 61287 | |
|
| deu-eng | newstest2018 | 0.66797 | 42.6 | 2998 | 67012 | |
|
| eng-deu | newstest2018 | 0.69605 | 46.5 | 2998 | 64276 | |
|
| deu-eng | newstest2019 | 0.63749 | 39.7 | 2000 | 39227 | |
|
| eng-deu | newstest2019 | 0.66751 | 42.9 | 1997 | 48746 | |
|
| deu-eng | newstest2020 | 0.61200 | 35.0 | 785 | 38220 | |
|
| eng-deu | newstest2020 | 0.60411 | 32.3 | 1418 | 52383 | |
|
| deu-eng | newstestB2020 | 0.61255 | 35.1 | 785 | 37696 | |
|
| eng-deu | newstestB2020 | 0.59513 | 31.8 | 1418 | 53092 | |
|
|
|
## Citation Information |
|
|
|
* Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.) |
|
|
|
``` |
|
@inproceedings{tiedemann-thottingal-2020-opus, |
|
title = "{OPUS}-{MT} {--} Building open translation services for the World", |
|
author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh}, |
|
booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation", |
|
month = nov, |
|
year = "2020", |
|
address = "Lisboa, Portugal", |
|
publisher = "European Association for Machine Translation", |
|
url = "https://aclanthology.org/2020.eamt-1.61", |
|
pages = "479--480", |
|
} |
|
|
|
@inproceedings{tiedemann-2020-tatoeba, |
|
title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}", |
|
author = {Tiedemann, J{\"o}rg}, |
|
booktitle = "Proceedings of the Fifth Conference on Machine Translation", |
|
month = nov, |
|
year = "2020", |
|
address = "Online", |
|
publisher = "Association for Computational Linguistics", |
|
url = "https://aclanthology.org/2020.wmt-1.139", |
|
pages = "1174--1182", |
|
} |
|
``` |
|
|
|
## Acknowledgements |
|
|
|
The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland. |
|
|
|
## Model conversion info |
|
|
|
* transformers version: 4.16.2 |
|
* OPUS-MT git hash: 8b9f0b0 |
|
* port time: Fri Aug 12 23:58:31 EEST 2022 |
|
* port machine: LM0-400-22516.local |
|
|
