Add Token Classification / Named Entity Recongnition (NER) Example with KerasNLP

[awsaf49]

Issue Type

Feature Request

Keras Version

Keras 3

Current Behavior?

Token Classification, also known as Named Entity Recognition (NER), is a highly popular and intriguing problem in the field of Natural Language Processing (NLP). It would greatly benefit the community to have an example on keras.io utilizing KerasNLP.

• While there is an existing example titled Named Entity Recognition with Transformers, it employs a simplistic approach to NER. For instance, instead of utilizing a tokenizer, it employs StringLookup, and rather than utilizing a pre-trained model, it implements a basic Transformer model. While this tutorial is informative, it may not yield competitive performance.

• Also, there was a discussion about this on Add Token Classification Example for KerasNLP #1291 and Roadmap to Token Classification Tasks keras-nlp#927 almost a year ago, which suggested some changes to KerasNLP to include a token classification example. But those issues were closed.

Tutorial

I've recently published a notebook on Kaggle's "PII Data Detection" competition demonstrating the token classification task from scratch with KerasNLP which achieves very competitive performance. I would love to add it in keras.io. As this notebook was created for Kaggle competition, I'm open to suggestions to make it more suitable for keras.io.

I think this notebook can also serve as a potential solution to keras-team/keras-nlp#927 as I implemented components for token classification with KerasNLP that was discussed there.

Relevant log output

No response

[awsaf49]

cc: @fchollet @martin-gorner

[hertschuh]

@awsaf49 ,

That sounds great. Do you want to create an example for keras.io and submit a PR for it?