| title: Text Classification Model | |
| emoji: 🤗 | |
| colorFrom: blue | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 3.14.0 | |
| app_file: app.py | |
| pinned: false | |
| tags: | |
| - text-classification | |
| - sentiment-analysis | |
| - transformers | |
| - distilbert | |
| license: mit | |
| language: | |
| - en | |
| # 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 | |
| ```python | |
| 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 | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ## Local Testing | |
| ```bash | |
| python test_model.py | |
| ``` |