---
tags:
- multimodal-entailment
- generic

---
## Tensorflow Keras Implementation of Named Entity Recognition using Transformers.

This repo contains code using the model. [Named Entity Recognition using Transformers](https://keras.io/examples/nlp/ner_transformers/).

Credits: [Varun Singh](https://www.linkedin.com/in/varunsingh2/) - Original Author

HF Contribution: [Rishav Chandra Varma](https://huggingface.co/reichenbach)  

## Background Information

### Introduction

Named Entity Recognition (NER) is the process of identifying named entities in text. Example of named entities are: "Person", "Location", "Organization", "Dates" etc. NER is essentially a token classification task where every token is classified into one or more predetermined categories.

We will train a simple Transformer based model to perform NER. We will be using the data from CoNLL 2003 shared task. For more information about the dataset, please visit the [dataset website](https://www.clips.uantwerpen.be/conll2003/ner/). However, since obtaining this data requires an additional step of getting a free license, we will be using HuggingFace's datasets library which contains a processed version of this [dataset](https://huggingface.co/datasets/conll2003).