Issue I’d like to run the sample code for Token Classification with W-NUT Emerging Entities on Google Colaboratory, but I cannot run it both CPU and GPU environment. How can I check default values of Trainer for each pre-trained model? Errors I didn’t set Target on my code. Where can I fix it and…

Did you get any solution for this? I am also facing same issue

I see you’re instantiating the model twice, one time providing num_labels, one time not. Note that any model in HuggingFace Transformers will have num_labels = 2 if not specified. In any case, you should initialize the model only once, as follows: from transformers import DistilBertForTokenClassif…

Different question about the same tutorial - but im following tensoflow version. I managed to follow and train the model, first using example data then with my own sentences and tags. But I cant figure out how to run model.predict on arbitrary string - how to format the input ?

Fine-tuning: Token Classification with W-NUT Emerging Entities

Beginners

nielsr October 13, 2021, 1:03pm 5

You can check out this thread regarding performing inference with NER models: Decoding the predicted output array in distilbertbase uncased model for NER - #2 by nielsr

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Fine-tuning: Token Classification with W-NUT Emerging Entities

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