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---
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license: mit
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language:
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- de
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- en
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tags:
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- translation
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- pytorch
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datasets:
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- multi30k
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metrics:
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- bleu
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model-index:
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- name: multi30k
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results:
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- task:
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type: translation
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dataset:
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type: multi30k
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name: multi30k-de-en
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metrics:
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- type: bleu
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value: 33.468
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name: Test BLEU
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args: n_gram=4
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---
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# Seq2seq + Attention
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[](https://colab.research.google.com/github/msarmi9/dlxp/blob/master/colab/seq2seq.ipynb)
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Pytorch implementation of [Neural Machine Translation by Jointly Learning to Align and Translate](https://arxiv.org/abs/1409.0473). Trained on the [Multi30k-de-en](http://www.statmt.org/wmt16/multimodal-task.html#task1) dataset with sentencepiece as the tokenizer.
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Here's the attention heatmap of a random sample from the test set:
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