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Deep text matching

Text matching using several deep models.

Implemented models

  • Baseline model: Word vectors averaging + Fully connected feed-forward layers.
  • Deep Bi-LSTMs based model.
  • RNMT+ encoder based model.
  • Transformer encoder based model.
  • Multi head attention based model.

Get started

  • The main entry point is at train.py.
  • Test with very small dataset using test.py before training.
  • Grid search hyper-parameters with grid_search.py.
  • Use apply.py to load trained model.