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Model Architecture:

The model is a sequential model in TensorFlow/Keras. Input Layer: A Flatten layer that transforms the input images of size (28, 28) into a flat vector. Hidden Layers: The model has two fully connected hidden layers with 512 and 256 neurons, respectively, using the ReLU activation function. Output Layer: A fully connected layer with 10 neurons using the Softmax activation function for the task of classifying into 10 clothing categories in Fashion MNIST. Model Statistics: Loss on the test dataset: 0.4328601062297821. Accuracy on the test dataset: 0.8863000273704529. I'm still learning, in this model I'm trying to use validation set

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Dataset used to train elontusk404/fashion_mnist_model_accurace_0_88