Just one issue, it seems in a03 TextRNN, the result part (self.predictions) does not support multi-label classification. There is a lot to change if I want to adapt it to a multi-label classification task. Also the inference part is mostly about single label classification.
UPDATE: if you want to try a model now, you can go to folder 'a02_TextCNN', run 'python -u p7_TextCNN_train.py', it will use sample data to train a model, and print loss and F1 score periodically.
Thank you for sharing these wonderful codes!
Just one issue, it seems in a03 TextRNN, the result part (self.predictions) does not support multi-label classification. There is a lot to change if I want to adapt it to a multi-label classification task. Also the inference part is mostly about single label classification.
Best wishes, Hang