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---
language: en
tags:
- token-classification
- named-entity-recognition
- bert
- transformers
license: mit
datasets:
- conll2003
---
# Token Classification Model
## Description
This project involves developing a machine learning model for token classification, specifically for Named Entity Recognition (NER). Using a fine-tuned BERT model from the Hugging Face library, this system classifies tokens in text into predefined categories like names, locations, and dates.
The model is trained on a dataset annotated with entity labels to accurately classify each token. This token classification system is useful for information extraction, document processing, and conversational AI applications.
## Technologies Used
### Dataset
- **Source:** Kaggle: conll2003
- **Purpose:** Contains text data with annotated entities for token classification.
### Model
- **Base Model:** BERT (bert-base-uncased)
- **Library:** Hugging Face transformers
- **Task:** Token Classification (Named Entity Recognition)
### Approach
#### Preprocessing:
- Load and preprocess the dataset.
- Tokenize the text data and align labels with tokens.
#### Fine-Tuning:
- Fine-tune the BERT model on the token classification dataset.
#### Training:
- Train the model to classify each token into predefined entity labels.
#### Inference:
- Use the trained model to predict entity labels for new text inputs.
### Key Technologies
- **Deep Learning (BERT):** For advanced token classification and contextual understanding.
- **Natural Language Processing (NLP):** For text preprocessing, tokenization, and entity recognition.
- **Machine Learning Algorithms:** For model training and prediction tasks.
## Streamlit App
You can view and interact with the Streamlit app for token classification [here](https://huggingface.co/spaces/AdilHayat173/token_classifcation).
## Examples
Here are some examples of outputs from the model:
## Google Colab Notebook
You can view and run the Google Colab notebook for this project [here](https://colab.research.google.com/drive/1GYVlIToQ_lnT8XEjGrR2WFkUQWpWXgQi#scrollTo=ZlyX1Lgn8gjj).
## Acknowledgements
- Hugging Face for transformer models and libraries.
- Streamlit for creating the interactive web interface.
- [Your Dataset Provider] for the token classification dataset.
## Author
- AdilHayat
- [Hugging Face Profile](https://huggingface.co/AdilHayat173)
- [GitHub Profile](https://github.com/AdilHayat21173)
## Feedback
If you have any feedback, please reach out to us at hayatadil300@gmail.com.
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