This is a trained model for handwriting recognition using **hojjatk/mnist-dataset** dataset.

    ## Usage
    ```python
    model = torch.load("mnsit_digit_nn")
    model.eval()
    ```

    ## Training Param:
    epochs = 1
    batch_size = 64
    learning_rate = 0.001

    ## Model Architectue:
    ['(conv1): Conv2d(1, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))', '(conv2): Conv2d(16, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))', '(pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)', '(fc1): Linear(in_features=1568, out_features=128, bias=True)', '(fc2): Linear(in_features=128, out_features=10, bias=True)']
    
    ## Evaluation Results
    - Accuracy: 0.96
    - Precision: 0.96
    - Recall: 0.96