Open sanazjb opened 3 years ago
Hi!
Yes it should be possible to run our code for de-noising using the auxiliary noise model whilst using BERT for training the classifier. You will need to change the model
class by instantiating a BERT-like model, which can be done using the Huggingface transformers repository. The track_training_loss
function and BetaMixture1D
class that implement the de-noising loss and fitting of the BMM just consider the predictions made by the model M which is defined in the text_pred
class function. Please reach out if you have any further questions and let us know if this works for you.
Hello, thanks for the code. I was wondering if it is possible to use your code for noise reduction, whilst using BERT to train the classifier.