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---
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.
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