File size: 1,839 Bytes
b39a7ab 076fc63 b39a7ab 076fc63 b39a7ab 076fc63 b39a7ab 076fc63 b39a7ab 7d74ea5 076fc63 91ef97b 7d74ea5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 |
---
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 |
|