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