--- 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**. - πŸ“¦ **Model Type**: Custom CNN (ResNet-inspired) - 🐢🐱 **Task**: Binary Image Classification (Cat vs. Dog) - 🧠 **Trainable Parameters**: ~1.2 million - πŸ–ΌοΈ **Input Resolution**: 224x224 - πŸ‹οΈ **Training Data**: ~20,000 labeled cat and dog images - 🎯 **Validation Accuracy**: ~92% MozieFinder was trained from scratch β€” no pre-trained weights were used β€” 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.