DeepInEvil/topic_lstm_torch

RNN-based short text classification

• This is for multi-class short text classification.
• Model is built with Word Embedding, LSTM, and Fully-connected layer by Pytorch.
• A mini-batch is created by 0 padding and processed by using torch.nn.utils.rnn.PackedSequence.
• Cross-entropy Loss + Adam optimizer.

Model

• Embedding --> Dropout --> LSTM --> Dropout --> FC.

Preprocessing

• The following command will download the dataset used in Learning to Classify Short and Sparse Text & Web with Hidden Topics from Large-scale Data Collections from here and process it for training.

python preprocessing.py

Training

• The following command starts training. Run it with -h for optional arguments.

python main.py