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Model Card Updation
- multimodal-entailment
- generic
## Tensorflow Keras Implementation of Named Entity Recognition using Transformers.
This repo contains code using the model. [Named Entity Recognition using Transformers](
Credits: [Varun Singh]( - Original Author
HF Contribution: [Rishav Chandra Varma](
## 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]( 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](