Text Classification Model
This model performs sentiment analysis using a pre-trained transformer model fine-tuned on a custom dataset.
Features
- Sentiment analysis (positive/negative)
- Easy-to-use API
- Preprocessing included
- Configurable confidence threshold
Usage
from text_classifier import TextClassifier
classifier = TextClassifier()
result = classifier.predict("This is a great product!")
print(result)
Model Details
- Architecture: DistilBERT
- Dataset: SST-2 (Stanford Sentiment Treebank)
- Accuracy: ~86% (on SST-2 test set)
Hugging Face Space
This model can be deployed as a Hugging Face Space with a Gradio interface for easy interaction.
Installation
pip install -r requirements.txt
Local Testing
python test_model.py