The MNIST dataset was used to train a neural network having a single linear layer with SoftMax employed in the criterion function (Cross Entropy Loss) to classify handwritten digits in classes 0 to 9. The model yielded a 92% accuracy on the MNIST test dataset in 10 training epochs.
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The MNIST dataset was used to train a neural network having a single linear layer with SoftMax employed in the criterion function (Cross Entropy Loss) to classify handwritten digits in classes 0 to 9. The model yielded a 92% accuracy on the MNIST test dataset in 10 training epochs.
sharmeen-k/Digit_Classification_Softmax
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The MNIST dataset was used to train a neural network having a single linear layer with SoftMax employed in the criterion function (Cross Entropy Loss) to classify handwritten digits in classes 0 to 9. The model yielded a 92% accuracy on the MNIST test dataset in 10 training epochs.
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