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PyTorch implementation of the paper "Attention Is All You Need". (NeurIPS 2017)

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Attention Is All You Need (Transformer)

PyTorch implementation of the paper 'Attention is all you need' (NeurIPS 2017)

Requirements

  • Python 3.6 >
  • PyTorch 1.4 >
  • Dataset: Multi30k
  • Features: Model, Framework agnostic

Results

  • Prediction result : results/pred.txt
  • 12 Epochs (with train loss 1.3013) : BLEU = 30.59, 63.6/38.1/25.5/17.0 (BP=0.956, ratio=0.957, hyp_len=11710, ref_len=12242)
  • 21 Epochs (with train loss 0.7675) : BLEU = 32.81, 63.5/39.1/26.6/17.9 (BP=0.994, ratio=0.994, hyp_len=12174, ref_len=12242)
  • 39 Epochs (with train loss 0.2197) : BLEU = 31.77, 62.9/37.6/25.3/17.1 (BP=1.000, ratio=1.007, hyp_len=12327, ref_len=12242)

References

[1] Transformer in DGL (https://github.com/dmlc/dgl/tree/master/examples/pytorch/transformer)

[2] Multi30k (https://www.aclweb.org/anthology/W16-3210/)

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PyTorch implementation of the paper "Attention Is All You Need". (NeurIPS 2017)

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