| title: News Source Classifier | |
| emoji: 📰 | |
| colorFrom: blue | |
| colorTo: red | |
| sdk: fastapi | |
| sdk_version: 0.95.2 | |
| app_file: app.py | |
| pinned: false | |
| language: en | |
| license: mit | |
| tags: | |
| - text-classification | |
| - news-classification | |
| - LSTM | |
| - tensorflow | |
| pipeline_tag: text-classification | |
| widget: | |
| - example_title: "Crime News Headline" | |
| text: "Wife of murdered Minnesota pastor hired 3 men to kill husband after affair: police" | |
| - example_title: "Science News Headline" | |
| text: "Scientists discover breakthrough in renewable energy research" | |
| - example_title: "Political News Headline" | |
| text: "Presidential candidates face off in heated debate over climate policies" | |
| model-index: | |
| - name: News Source Classifier | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: Custom Dataset | |
| type: Custom | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.82 | |
| # News Source Classifier | |
| This model classifies news headlines as either Fox News or NBC News using an LSTM neural network. | |
| ## Model Description | |
| - **Model Architecture**: LSTM Neural Network | |
| - **Input**: News headlines (text) | |
| - **Output**: Binary classification (Fox News vs NBC) | |
| - **Training Data**: Large collection of headlines from both news sources | |
| - **Performance**: Achieves approximately 82% accuracy on the test set | |
| ## Usage | |
| You can use this model through the FastAPI endpoint: | |
| ```python | |
| import requests | |
| # Make a prediction | |
| response = requests.post( | |
| "https://huggingface.co/Jiahuita/NewsSourceClassification", | |
| json={"text": "Your news headline here"} | |
| ) | |
| print(response.json()) |