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