Hi, I managed to create a model using BiDAF and Pytorch.
BiDAF: Bi-Directional Attention Flow

  
      
      GitHub
  
  
    

galsang/BiDAF-pytorch 11

Re-implementation of BiDAF(Bidirectional Attention Flow for Machine Comprehension, Minjoon Seo et al., ICLR 2017) on PyTorch. - galsang/BiDAF-pytorch


  
  
    
    
  
  


The model has been trained on SQuAD: The Stanford Question Answering Dataset (https://rajpurkar.github.io/SQuAD-explorer/ 14)
Now, I would like to do transfer learning on a different context - financial regulation documents
My question is can anyone provide a ‘big picture’ view on what I should to to enable transfer learning so that the model can answer questions in relation to financial documents?
For example, do I have to create question answers pair with regards to the financial documents manually? If yes, do I have to clean up the documents (there are hundreds of them) and what software/technique should I use to clean up the data?
Any links and resources to read up?