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adityak6798 / Transformers-For-Negation-and-Speculation

This is the code for Negation and Speculation Cue Detection and Scope Resolution using BERT, XLNet and RoBERTa
MIT License
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Wondering if you have the pre-trained model #1

Closed ma7555 closed 4 years ago

ma7555 commented 4 years ago

Hello there,

Thanks so much for taking the time to write and share this code. I was asking if you already have trained this model and willing to share it.

Another thing is that the notebook is very helpful but it is too long to catch up with including parts that should have been imported from libraries instead of copied/pasted.

Looking forward for your colaboration

adityak6798 commented 4 years ago

Hey, I haven't saved a copy of the pre-trained model, but you should be able to train one on colab using the code in under an hour for most variants that you might want, just by changing the appropriate global variables.

Some parts have been copy-pasted as the code was originally written when certain components like XLNetForTokenClassification and RoBERTaForTokenClassification weren't available in the huggingface repo, hence I had to manually copy paste certain class definitions which weren't accessible through imports. Hence, the code length is fairly long. I have divided it into blocks though, which should make it fairly easy to follow along.

ma7555 commented 4 years ago

Hi adityak, thanks for coming back to me.

We want to do the training with the bioscope corpus, however the XML format it is found on is very unfriendly for me. wondering if you have managed to parse it?

adityak6798 commented 4 years ago

The parsing code is included in the 'bioscope' method of 'Data' class. You can input the path to the bioscope corpus file and get the processed output in the form of a data object.

ma7555 commented 4 years ago

Okay amazing, will take a look