| language: | |
| - en | |
| - hi | |
| - multilingual | |
| license: cc-by-4.0 | |
| tags: | |
| - translation | |
| - opus-mt-tc | |
| model-index: | |
| - name: opus-mt-tc-base-en-hi | |
| results: | |
| - task: | |
| type: translation | |
| name: Translation eng-hin | |
| dataset: | |
| name: tatoeba-test-v2021-08-07 | |
| type: tatoeba_mt | |
| args: eng-hin | |
| metrics: | |
| - type: bleu | |
| value: 22.2 | |
| name: BLEU | |
| # Opus Tatoeba English-Hindi | |
| *This model was obtained by running the script [convert_marian_to_pytorch.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/marian/convert_marian_to_pytorch.py). The original models were trained by [J�rg Tiedemann](https://blogs.helsinki.fi/tiedeman/) using the [MarianNMT](https://marian-nmt.github.io/) library. See all available `MarianMTModel` models on the profile of the [Helsinki NLP](https://huggingface.co/Helsinki-NLP) group.* | |
| * dataset: opus+bt | |
| * model: transformer-align | |
| * source language(s): eng | |
| * target language(s): hin | |
| * model: transformer-align | |
| * pre-processing: normalization + SentencePiece (spm32k,spm32k) | |
| * download: [opus+bt-2021-04-10.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hin/opus+bt-2021-04-10.zip) | |
| * test set translations: [opus+bt-2021-04-10.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hin/opus+bt-2021-04-10.test.txt) | |
| * test set scores: [opus+bt-2021-04-10.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hin/opus+bt-2021-04-10.eval.txt) | |
| ## Benchmarks | |
| | testset | BLEU | chr-F | #sent | #words | BP | | |
| |---------|-------|-------|-------|--------|----| | |
| | newsdev2014.eng-hin | 13.9 | 0.421 | 520 | 9538 | 1.000 | | |
| | newstest2014-hien.eng-hin | 17.4 | 0.442 | 2507 | 60878 | 0.989 | | |
| | Tatoeba-test.eng-hin | 22.2 | 0.485 | 5000 | 32904 | 1.000 | | |
| | tico19-test.eng-hin | 30.6 | 0.539 | 2100 | 62738 | 0.988 | | |