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| title: Comment Toxicity Detector | |
| emoji: 📈 | |
| colorFrom: red | |
| colorTo: pink | |
| sdk: gradio | |
| sdk_version: 4.31.5 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # Comment Toxicity Detector | |
| This project implements a sentiment analysis model that’s capable of detecting different types of toxicity like threats, obscenity, insults, and identity-based hate of a given comment. An LSTM-based model has been trained on 153 thousand sequence. | |
| ## Project Structure | |
| - __01. Data Preparation:__ | |
| * `Data Collection`: The [dataset](https://www.kaggle.com/datasets/julian3833/jigsaw-toxic-comment-classification-challenge) has been collected from the [Toxic Comment Classificatio Challenge](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge) held on Kaggle. | |
| * `Data Cleaning & Preprocessing`: | |
| - Vectorized the data utilizing "TextVectorization" from keras | |
| - Prepared a tensorflow dataset for model training | |
| - __02. Model Training:__ | |
| * A Bidirectional LSTM model with an embedding layer has been trained on the preprocessed data. | |
| - __03. App Deployment:__ | |
| * Developed a web-app with Gradio interface | |
| * Deployed the [App](https://huggingface.co/spaces/mazed/Comment_Toxicity_Detector) in HuggingFace Spaces. | |
| - `requirements.txt`: Contains the dependencies needed for the project: | |
| - `pandas` | |
| - `gradio` | |
| - `tensorflow==2.15.0` | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |