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README.md
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- translation
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---
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| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |
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| English-Greek | lighteternal/SSE-TUC-mt-en-el-cased | translation | Apache2 |Opus, CC-Matrix |BLEU, chrF |
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# English to Greek NMT from Hellenic Army Academy (SSE) and Technical University of Crete (TUC)
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## Model description
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Trained using the Fairseq framework, transformer_iwslt_de_en architecture.\
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BPE segmentation (20k codes).\
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Mixed-case model.
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```
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from transformers import FSMTTokenizer, FSMTForConditionalGeneration
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## Eval results
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Results on Tatoeba testset (EN-EL):
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| BLEU | chrF |
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| ------ | ------ |
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| 76.9 | 0.733 |
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Results on XNLI parallel (EN-EL):
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| BLEU | chrF |
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| ------ | ------ |
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## English to Greek NMT from Hellenic Army Academy (SSE) and Technical University of Crete (TUC)
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* source languages: en
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* target languages: el
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* licence: apache-2.0
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* dataset: opus, ccmatric
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* model: transformer(fairseq)
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* pre-processing: tokenization+BPE segmentation
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* metrics: bleu, chrf
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### Model description
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Trained using the Fairseq framework, transformer_iwslt_de_en architecture.\
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BPE segmentation (20k codes).\
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Mixed-case model.
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### How to use
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```
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from transformers import FSMTTokenizer, FSMTForConditionalGeneration
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## Eval results
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Results on Tatoeba testset (EN-EL):
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| BLEU | chrF |
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| ------ | ------ |
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| 76.9 | 0.733 |
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Results on XNLI parallel (EN-EL):
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| BLEU | chrF |
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| ------ | ------ |
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