GiladtheFixer/my_Mnist_Model

MNIST Classification Model

An improved CNN model for handwritten digit recognition, trained on the MNIST dataset.

Model Architecture

• Uses Convolutional layers (CNN)
• Data Augmentation for improved performance
• Batch Normalization
• Dropout for preventing Overfitting
• Dense layers with ReLU activation

Parameters

• Optimizer: Adam (lr=0.001)
• Loss: Sparse Categorical Crossentropy
• Metrics: Accuracy
• Epochs: 20 (with Early Stopping)
• Batch Size: 32

Performance

Test Accuracy: 0.9884