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---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
{}
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Model Details
This model classifies news headlines as either NBC or Fox News.
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** Jack Bader, Kaiyuan Wang, Pairan Xu
- **Taks:** Binary classification (NBC News vs. Fox News)
- **Preprocessing:** TF-IDF vectorization applied to the text data
- stop_words = "english"
- max_features = 1000
- **Model type:** Random Forest
- **Freamwork:** Scikit-learn
-
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
- Accuracy Score
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