Based on the repository TextClassifiers by datnnt1997. Textclassifiers: Collection of Text Classification/Document Classification/Sentence Classification/Sentiment Analysis models for PyTorch

Install dependencies:
pip3 install -r requirements.txt

python3 run.py --mode train --config configs/fasttext_config.yaml

• FastText released with the paper Bag of tricks for efficient text classification by Joulin, Armand, et al.
• TextRNN
• TextCNN released with the paper Convolutional neural networks for sentence classification by Kim, Yoon.
• RCNN released with the paper Recurrent convolutional neural networks for text classification by Lai, Siwei, et al.
• LSTM + Attention released with the paper Text classification research with attention-based recurrent neural networks by Du, Changshun, and Lei Huang.
• Transformer released with the paper Attention is all you need by Vaswani, Ashish, et al.

[1] Joulin, Armand, Edouard Grave, and Piotr Bojanowski Tomas Mikolov. "Bag of Tricks for Efficient Text Classification." EACL 2017 (2017): 427.

[2] Kim, Yoon. "Convolutional Neural Networks for Sentence Classification." Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2014.

[3] Lai, Siwei, et al. "Recurrent convolutional neural networks for text classification." In Proc. Conference of the Association for the Advancement of Artificial Intelligence (AAAI). 2015.

[4] Du, Changshun, and Lei Huang. "Text classification research with attention-based recurrent neural networks." International Journal of Computers Communications & Control 13.1 (2018): 50-61.

[5] Vaswani, Ashish, et al. "Attention is all you need." Proceedings of the 31st International Conference on Neural Information Processing Systems. Curran Associates Inc., 2017.