Text matching using several deep 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.
- 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.