---
language: en
license: mit
datasets: [Cats-Dogs]
metrics: [accuracy, f1, precision, recall]
---

# 🐱🐶 Transfer Learning on AlexNet for Cats vs. Dogs Classification

This model fine-tunes **AlexNet** using Transfer Learning to classify images into two categories: **Cats** and **Dogs**.

## **📝 Model Details**
- **Pre-trained Model:** AlexNet  
- **Dataset Used:** Cats-Dogs  
- **Batch Size:** 8  
- **Learning Rate:** 0.001  
- **Epochs:** 5  

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## **📌 Baseline Performance (Before Transfer Learning)**  
**Validation Accuracy:** **40.66%**  
- **Precision:** 0.3983  
- **Recall:** 0.4066  
- **F1-score:** 0.3942  

- Confusion Matrix:
 [[659   1841]
 [1126   1374]]
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## **✅ Performance After Training**  
**Training Accuracy:** **92.40%**  
- **Precision:** 0.9250  
- **Recall:** 0.9240  
- **F1-score:** 0.9240  

**Confusion Matrix:**
 [[9486   514]
 [1006   8994]]


**Validation Accuracy:** **94.10%**  
- **Precision:** 0.9425  
- **Recall:** 0.9410  
- **F1-score:** 0.9410  

**Confusion Matrix:**
 [[2425   75]
 [ 220   2280]]

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You can download the model from [Hugging Face](https://huggingface.co/Wolverine001/Alexnet-TransferLearning).