Skip to content

About

GuardRail Neural Inspector — In-browser Keras Dense(96)->Dense(32)->Sigmoid text moderation engine trained on UCI SMS Spam (99.1% accuracy) with token attribution

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Repository files navigation

Keras Content Moderation System

Real deep learning portfolio project for text moderation. It trains a Keras neural network on the UCI SMS Spam Collection dataset, exports the learned vocabulary and weights, and runs actual model inference in the web app.

Model

  • Dataset: UCI SMS Spam Collection
  • Framework: TensorFlow / Keras
  • Architecture: bag-of-words input -> Dense(96, ReLU) -> Dropout -> Dense(32, ReLU) -> Dense(1, sigmoid)
  • Test accuracy: 99.1%
  • Test F1: 96.5%
  • Exported artifacts:
    • public/model/keras_sms_moderation.keras
    • public/model/moderation_model.json
    • reports/keras_moderation_metrics.json

Train

python scripts/train_keras_moderation.py

Run

npm install
npm run dev

Deploy

npm run build
vercel deploy --prod

About

GuardRail Neural Inspector — In-browser Keras Dense(96)->Dense(32)->Sigmoid text moderation engine trained on UCI SMS Spam (99.1% accuracy) with token attribution

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages