machine-translation-nar-de-en-0002

## Use Case and High-Level Description

This is a Deutsch-English machine translation model based on non-autoregressive Transformer topology.

Tokenization occurs using the SentencePieceBPETokenizer (see the demo code for implementation details) and the enclosed tokenizer_src and tokenizer_tgt folders.

## Specification

Metric Value
GOps 23.19
MParams 77.47
Source framework PyTorch*

## Accuracy

The quality metrics were calculated on the wmt19-en-de dataset (test split in lower case).

Metric Value
BLEU 21.4 %

## Input

name: tokens shape: 1, 150 description: sequence of tokens (integer values) representing the tokenized sentence. The sequence structure is as follows (<s>, </s> and <pad> should be replaced by corresponding token IDs as specified by the dictionary): <s> + tokenized sentence + </s> + (<pad> tokens to pad to the maximum sequence length of 150)

## Output

name: pred shape: 1, 200 description: sequence of tokens (integer values) representing the tokenized translation. The sequence structure is as follows (<s>, </s> and <pad> should be replaced by corresponding token IDs as specified by the dictionary): <s> + tokenized sentence + </s> + (<pad> tokens to pad to the maximum sequence length of 150)

## Legal Information

[*] Other names and brands may be claimed as the property of others.