louiecerv/cats_dogs_recognition_tf_cnn

Cats and Dogs Classifier This model is a Convolutional Neural Network (CNN) trained to classify images of cats and dogs. It was trained on the louiecerv/cats_dogs_dataset dataset.

Model Architecture 3 Convolutional layers with ReLU activation and Batch Normalization MaxPooling layers after each convolutional layer Dropout layer after the second convolutional layer Global Average Pooling layer Fully connected layer with 256 units and ReLU activation Output layer with softmax activation for 2 classes (cats and dogs) Training The model was trained using the Adam optimizer with a learning rate of 0.001 and Sparse Categorical Crossentropy loss. It was trained for 5 epochs with a batch size of 32.

Performance The model achieved an accuracy of X% on the validation set.

Usage To use this model, you can load it using TensorFlow and make predictions on new images of cats and dogs.