README.md

metadata

license: mit
language:
  - en
metrics:
  - accuracy
  - bertscore
library_name: keras
tags:
  - dogs
  - cats
  - mozie
  - detection
pipeline_tag: image-classification

🐾 MozieFinder

MozieFinder is a lightweight convolutional neural network (CNN) model built from scratch using TensorFlow, designed to classify images as either cats or dogs.

• 📦 Model Type: Custom CNN (ResNet-inspired)
• 🐶🐱 Task: Binary Image Classification (Cat vs. Dog)
• 🧠 Trainable Parameters: ~1.2 million
• 🖼️ Input Resolution: 224x224
• 🏋️ Training Data: ~20,000 labeled cat and dog images
• 🎯 Validation Accuracy: ~92%

MozieFinder was trained from scratch — no pre-trained weights were used — as a demonstration of how to build a robust image classification model end-to-end.

⚠️ Disclaimer: This model card was written by the model creator. It has not been officially reviewed by TensorFlow or affiliated teams.