Hey guys, I’m following the steps described here: https://huggingface.co/transformers/custom_datasets.html#token-classification-with-w-nut-emerging-entities 8 and fine-tune with native tensorflow ( see https://huggingface.co/transformers/custom_datasets.html#ft-native 1) .
During training I’d like to add a metric to see how the model is performing. Currently I have added SparseCategoricalAccuracy but it gets stuck at an accuracy of around 0.2. I can have the Distilbertlayer trainable True or False, it doesn’t make a difference.
What can I do now? What metric would you suggest and what performance can I expect?
Also, do you recommend to set all layer to trainable or only the final Dense layer?
Thanks! Have a nice day!