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Character based Temporal Convolutional Networks + Attention Layer

TCN with attention

Temporal Convolutional Network with attention layer

Concept of model is mostly like Simple Neural Attentive Meta-Learner (SNAIL). But in this model, attention layer is on every top of convolutions layers. And attention size is differ from SNAIL.

Result

Dataset: Agnews without pre-processing

  • with attention: 0.82
  • without attention: 0.81

My thoughts on result

Most of simple models on agnews shows 0.81 accuracy. (Which tested on A Structured Self-Attentive Sentence Embedding, TagSpace and it uses word based embedding)

So 0.82 accuracy with character based model seems worthiness.