
### opus-mt-en-de


## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Citation Information](#citation-information)
- [How to Get Started With the Model](#how-to-get-started-with-the-model)

## Model Details
**Model Description:**
- **Developed by:** Language Technology Research Group at the University of Helsinki
- **Model Type:** Translation
- **Language(s):**  
  - Source Language: English
  - Target Language: German 
- **License:** CC-BY-4.0
- **Resources for more information:**
  - [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
  

## Uses

#### Direct Use

This model can be used for translation and text-to-text generation.


## Risks, Limitations and Biases



**CONTENT WARNING: Readers should be aware this section contains 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)).

Further details about the dataset for this model can be found in the OPUS readme: [en-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-de/README.md)


#### Training Data
##### Preprocessing
* pre-processing: normalization + SentencePiece

* dataset: [opus](https://github.com/Helsinki-NLP/Opus-MT)
* download original weights: [opus-2020-02-26.zip](https://object.pouta.csc.fi/OPUS-MT-models/en-de/opus-2020-02-26.zip)

* test set translations: [opus-2020-02-26.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-de/opus-2020-02-26.test.txt)

## Evaluation

#### Results

* test set scores: [opus-2020-02-26.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-de/opus-2020-02-26.eval.txt)


#### Benchmarks

| testset               | BLEU  | chr-F |
|-----------------------|-------|-------|
| newssyscomb2009.en.de 	| 23.5 	| 0.540 |
| news-test2008.en.de 	| 23.5 	| 0.529 |
| newstest2009.en.de 	| 22.3 	| 0.530 |
| newstest2010.en.de 	| 24.9 	| 0.544 |
| newstest2011.en.de 	| 22.5 	| 0.524 |
| newstest2012.en.de 	| 23.0 	| 0.525 |
| newstest2013.en.de 	| 26.9 	| 0.553 |
| newstest2015-ende.en.de 	| 31.1 	| 0.594 |
| newstest2016-ende.en.de 	| 37.0 	| 0.636 |
| newstest2017-ende.en.de 	| 29.9 	| 0.586 |
| newstest2018-ende.en.de 	| 45.2 	| 0.690 |
| newstest2019-ende.en.de 	| 40.9 	| 0.654 |
| Tatoeba.en.de 	| 47.3 	| 0.664 |



## Citation Information

```bibtex
@InProceedings{TiedemannThottingal:EAMT2020,
  author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
  title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
  booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
  year = {2020},
  address = {Lisbon, Portugal}
 }
```

## How to Get Started With the Model
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-de")

model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-de")

```





{"license": "cc-by-4.0", "tags": ["translation"]}
transformers pytorch tf jax rust marian text2text-generation translation en de license:cc-by-4.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #jax #rust #marian #text2text-generation #translation #en #de #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

### opus-mt-en-de


Table of Contents
-----------------


* Model Details
* Uses
* Risks, Limitations and Biases
* Training
* Evaluation
* Citation Information
* How to Get Started With the Model


Model Details
-------------


Model Description:


* Developed by: Language Technology Research Group at the University of Helsinki
* Model Type: Translation
* Language(s):
	+ Source Language: English
	+ Target Language: German
* License: CC-BY-4.0
* Resources for more information:
	+ GitHub Repo


Uses
----


#### Direct Use


This model can be used for translation and text-to-text generation.


Risks, Limitations and Biases
-----------------------------


CONTENT WARNING: Readers should be aware this section contains 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) and Bender et al. (2021)).


Further details about the dataset for this model can be found in the OPUS readme: en-de


#### Training Data


##### Preprocessing


* pre-processing: normalization + SentencePiece
* dataset: opus
* download original weights: URL
* test set translations: URL


Evaluation
----------


#### Results


* test set scores: URL


#### Benchmarks


testset: URL, BLEU: 23.5, chr-F: 0.540
testset: URL, BLEU: 23.5, chr-F: 0.529
testset: URL, BLEU: 22.3, chr-F: 0.530
testset: URL, BLEU: 24.9, chr-F: 0.544
testset: URL, BLEU: 22.5, chr-F: 0.524
testset: URL, BLEU: 23.0, chr-F: 0.525
testset: URL, BLEU: 26.9, chr-F: 0.553
testset: URL, BLEU: 31.1, chr-F: 0.594
testset: URL, BLEU: 37.0, chr-F: 0.636
testset: URL, BLEU: 29.9, chr-F: 0.586
testset: URL, BLEU: 45.2, chr-F: 0.690
testset: URL, BLEU: 40.9, chr-F: 0.654
testset: URL, BLEU: 47.3, chr-F: 0.664


How to Get Started With the Model
---------------------------------



### opus-mt-en-de


Table of Contents
-----------------


* Model Details
* Uses
* Risks, Limitations and Biases
* Training
* Evaluation
* Citation Information
* How to Get Started With the Model


Model Details
-------------


Model Description:


* Developed by: Language Technology Research Group at the University of Helsinki
* Model Type: Translation
* Language(s):
	+ Source Language: English
	+ Target Language: German
* License: CC-BY-4.0
* Resources for more information:
	+ GitHub Repo


Uses
---- #### Direct Use


This model can be used for translation and text-to-text generation.


Risks, Limitations and Biases
-----------------------------


CONTENT WARNING: Readers should be aware this section contains 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) and Bender et al. (2021)).


Further details about the dataset for this model can be found in the OPUS readme: en-de #### Training Data ##### Preprocessing


* pre-processing: normalization + SentencePiece
* dataset: opus
* download original weights: URL
* test set translations: URL


Evaluation
---------- #### Results


* test set scores: URL #### Benchmarks


testset: URL, BLEU: 23.5, chr-F: 0.540
testset: URL, BLEU: 23.5, chr-F: 0.529
testset: URL, BLEU: 22.3, chr-F: 0.530
testset: URL, BLEU: 24.9, chr-F: 0.544
testset: URL, BLEU: 22.5, chr-F: 0.524
testset: URL, BLEU: 23.0, chr-F: 0.525
testset: URL, BLEU: 26.9, chr-F: 0.553
testset: URL, BLEU: 31.1, chr-F: 0.594
testset: URL, BLEU: 37.0, chr-F: 0.636
testset: URL, BLEU: 29.9, chr-F: 0.586
testset: URL, BLEU: 45.2, chr-F: 0.690
testset: URL, BLEU: 40.9, chr-F: 0.654
testset: URL, BLEU: 47.3, chr-F: 0.664


How to Get Started With the Model
---------------------------------
TAGS
#transformers #pytorch #tf #jax #rust #marian #text2text-generation #translation #en #de #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### opus-mt-en-de


Table of Contents
-----------------


* Model Details
* Uses
* Risks, Limitations and Biases
* Training
* Evaluation
* Citation Information
* How to Get Started With the Model


Model Details
-------------


Model Description:


* Developed by: Language Technology Research Group at the University of Helsinki
* Model Type: Translation
* Language(s):
	+ Source Language: English
	+ Target Language: German
* License: CC-BY-4.0
* Resources for more information:
	+ GitHub Repo


Uses
---- #### Direct Use


This model can be used for translation and text-to-text generation.


Risks, Limitations and Biases
-----------------------------


CONTENT WARNING: Readers should be aware this section contains 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) and Bender et al. (2021)).


Further details about the dataset for this model can be found in the OPUS readme: en-de #### Training Data ##### Preprocessing


* pre-processing: normalization + SentencePiece
* dataset: opus
* download original weights: URL
* test set translations: URL


Evaluation
---------- #### Results


* test set scores: URL #### Benchmarks


testset: URL, BLEU: 23.5, chr-F: 0.540
testset: URL, BLEU: 23.5, chr-F: 0.529
testset: URL, BLEU: 22.3, chr-F: 0.530
testset: URL, BLEU: 24.9, chr-F: 0.544
testset: URL, BLEU: 22.5, chr-F: 0.524
testset: URL, BLEU: 23.0, chr-F: 0.525
testset: URL, BLEU: 26.9, chr-F: 0.553
testset: URL, BLEU: 31.1, chr-F: 0.594
testset: URL, BLEU: 37.0, chr-F: 0.636
testset: URL, BLEU: 29.9, chr-F: 0.586
testset: URL, BLEU: 45.2, chr-F: 0.690
testset: URL, BLEU: 40.9, chr-F: 0.654
testset: URL, BLEU: 47.3, chr-F: 0.664


How to Get Started With the Model
---------------------------------
passage: TAGS
#transformers #pytorch #tf #jax #rust #marian #text2text-generation #translation #en #de #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
### opus-mt-en-de


Table of Contents
-----------------


* Model Details
* Uses
* Risks, Limitations and Biases
* Training
* Evaluation
* Citation Information
* How to Get Started With the Model


Model Details
-------------


Model Description:


* Developed by: Language Technology Research Group at the University of Helsinki
* Model Type: Translation
* Language(s):
	+ Source Language: English
	+ Target Language: German
* License: CC-BY-4.0
* Resources for more information:
	+ GitHub Repo


Uses
----#### Direct Use


This model can be used for translation and text-to-text generation.


Risks, Limitations and Biases
-----------------------------


CONTENT WARNING: Readers should be aware this section contains 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) and Bender et al. (2021)).


Further details about the dataset for this model can be found in the OPUS readme: en-de#### Training Data##### Preprocessing


* pre-processing: normalization + SentencePiece
* dataset: opus
* download original weights: URL
* test set translations: URL


Evaluation
----------#### Results


* test set scores: URL