A PyTorch implementation of a character-level convolutional neural network
Character Based CNN
This repo contains a PyTorch implementation of a character-level convolutional neural network for text classification.
The model architecture comes from this paper: https://arxiv.org/pdf/1509.01626.pdf
There are two variants: a large and a small. You can switch between the two by changing the configuration file.
This architecture has 6 convolutional layers:
| Layer | Large Feature | Small Feature | Kernel | Pool |
|---|---|---|---|---|
| 1 | 1024 | 256 | 7 | 3 |
| 2 | 1024 | 256 | 7 | 3 |
| 3 | 1024 | 256 | 3 | N/A |
| 4 | 1024 | 256 | 3 | N/A |
| 5 | 1024 | 256 | 3 | N/A |
| 6 | 1024 | 256 | 3 | 3 |
and 2 fully connected layers:
| Layer | Output Units Large | Output Units Small |
|---|---|---|
| 7 | 2048 | 1024 |
| 8 | 2048 | 1024 |
| 9 | Depends on the problem | Depends on the problem |
Video tutorial
If you’re interested in how character