Wolverine001/Alexnet_TransferLearning

🐱🐶 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.