You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
First of all, I want to thanks a lot for this awesome project. I have been meaning to get fairseq to do sequence tagging for the past few days. I was just trying to understand how I could do that, when I came across your project. I would like to contribute to the project in any way, if I can.
At a more general level, would you be able to explain what were the major changes that you made. I am trying to understand whether it would be possible to incorporate any downstream changes from fairseq or how hard would it be.
Specifically, can we implement simple models like BiLSTM-CRF using this? I saw that on the TO-DO list in the Read me, which means you have it in the pipeline. I could possible help you with that. Also, I was wondering whether we could make it such that we specify a generic encoder (transformer or LSTM) and whether or not we need a CRF layer on top of it to perform sequence tagging.
My personal aim is to also modify it to do multi task learning. I am hoping that the experience I gain doing this will help me with that as well.
Thanks
The text was updated successfully, but these errors were encountered:
@zeeshansayyed Thank you for your interest to contribute. what I did here is simply use the masked language modeling architectures (encoders) and tweaked them a bit for sequence tagging in the sequence_tagger module.
I believe you can start with a vanilla BiLSTM (CRF would probably be more work, but still possible), which would be a significant contribution to the repo. The way I see it is that you'll need to implement LSTM encoder-only architecture with a similar interface to SequenceTagger. You can create something like LSTMSequenceTagger with a fairseq.models.LSTMEncoder inside.
Hi @Mohammadkhalifa I opened an issue in the original fairseq repo asking about implementing the CRF tagger here. Do you have any thoughts on it? What I am mostly concerned about is having different implementations of forward while training and evaluation. If we do this, how will we have to change the generator code?
Thanks
Hi @Mohammadkhalifa
First of all, I want to thanks a lot for this awesome project. I have been meaning to get fairseq to do sequence tagging for the past few days. I was just trying to understand how I could do that, when I came across your project. I would like to contribute to the project in any way, if I can.
At a more general level, would you be able to explain what were the major changes that you made. I am trying to understand whether it would be possible to incorporate any downstream changes from fairseq or how hard would it be.
Specifically, can we implement simple models like BiLSTM-CRF using this? I saw that on the TO-DO list in the Read me, which means you have it in the pipeline. I could possible help you with that. Also, I was wondering whether we could make it such that we specify a generic encoder (transformer or LSTM) and whether or not we need a CRF layer on top of it to perform sequence tagging.
My personal aim is to also modify it to do multi task learning. I am hoping that the experience I gain doing this will help me with that as well.
Thanks
The text was updated successfully, but these errors were encountered: