Session 5: Introduction to Pytorch - MNIST Classifier
| Code Link |
|---|
| Google Colab |
Data Description
Model Description
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Layer (type) Output Shape Param #
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Conv2d-1 [-1, 32, 26, 26] 320
Conv2d-2 [-1, 64, 24, 24] 18,496
Conv2d-3 [-1, 128, 10, 10] 73,856
Conv2d-4 [-1, 256, 8, 8] 295,168
Linear-5 [-1, 50] 204,850
Linear-6 [-1, 10] 510
================================================================
Total params: 593,200
Trainable params: 593,200
Non-trainable params: 0
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Input size (MB): 0.00
Forward/backward pass size (MB): 0.67
Params size (MB): 2.26
Estimated Total Size (MB): 2.94
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Model Visualization
Training & Testing
Logs
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 1
Train: Loss=0.4035 Batch_id=117 Accuracy=43.25: 100%|██████████| 118/118 [00:34<00:00, 3.40it/s]
Test set: Average loss: 0.2886, Accuracy: 9154/10000 (91.54%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 2
Train: Loss=0.1115 Batch_id=117 Accuracy=92.75: 100%|██████████| 118/118 [00:27<00:00, 4.33it/s]
Test set: Average loss: 0.1006, Accuracy: 9697/10000 (96.97%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 3
Train: Loss=0.0739 Batch_id=117 Accuracy=95.98: 100%|██████████| 118/118 [00:27<00:00, 4.36it/s]
Test set: Average loss: 0.0644, Accuracy: 9814/10000 (98.14%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 4
Train: Loss=0.1233 Batch_id=117 Accuracy=96.94: 100%|██████████| 118/118 [00:27<00:00, 4.33it/s]
Test set: Average loss: 0.0518, Accuracy: 9836/10000 (98.36%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 5
Train: Loss=0.0437 Batch_id=117 Accuracy=97.28: 100%|██████████| 118/118 [00:27<00:00, 4.25it/s]
Test set: Average loss: 0.0442, Accuracy: 9850/10000 (98.50%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 6
Train: Loss=0.0982 Batch_id=117 Accuracy=97.68: 100%|██████████| 118/118 [00:27<00:00, 4.34it/s]
Test set: Average loss: 0.0438, Accuracy: 9849/10000 (98.49%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 7
Train: Loss=0.0239 Batch_id=117 Accuracy=98.05: 100%|██████████| 118/118 [00:27<00:00, 4.33it/s]
Test set: Average loss: 0.0346, Accuracy: 9890/10000 (98.90%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 8
Train: Loss=0.0843 Batch_id=117 Accuracy=98.20: 100%|██████████| 118/118 [00:27<00:00, 4.33it/s]
Test set: Average loss: 0.0346, Accuracy: 9886/10000 (98.86%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 9
Train: Loss=0.0354 Batch_id=117 Accuracy=98.30: 100%|██████████| 118/118 [00:27<00:00, 4.37it/s]
Test set: Average loss: 0.0311, Accuracy: 9901/10000 (99.01%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 10
Train: Loss=0.0389 Batch_id=117 Accuracy=98.39: 100%|██████████| 118/118 [00:27<00:00, 4.27it/s]
Test set: Average loss: 0.0325, Accuracy: 9895/10000 (98.95%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 11
Train: Loss=0.0608 Batch_id=117 Accuracy=98.51: 100%|██████████| 118/118 [00:27<00:00, 4.35it/s]
Test set: Average loss: 0.0296, Accuracy: 9899/10000 (98.99%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 12
Train: Loss=0.0337 Batch_id=117 Accuracy=98.65: 100%|██████████| 118/118 [00:27<00:00, 4.35it/s]
Test set: Average loss: 0.0263, Accuracy: 9915/10000 (99.15%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 13
Train: Loss=0.0673 Batch_id=117 Accuracy=98.66: 100%|██████████| 118/118 [00:27<00:00, 4.33it/s]
Test set: Average loss: 0.0271, Accuracy: 9911/10000 (99.11%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 14
Train: Loss=0.0157 Batch_id=117 Accuracy=98.66: 100%|██████████| 118/118 [00:27<00:00, 4.36it/s]
Test set: Average loss: 0.0247, Accuracy: 9912/10000 (99.12%)
Adjusting learning rate of group 0 to 1.0000e-02.
Epoch 15
Train: Loss=0.0438 Batch_id=117 Accuracy=98.81: 100%|██████████| 118/118 [00:27<00:00, 4.28it/s]
Test set: Average loss: 0.0253, Accuracy: 9920/10000 (99.20%)
Adjusting learning rate of group 0 to 1.0000e-03.
Epoch 16
Train: Loss=0.0872 Batch_id=117 Accuracy=99.02: 100%|██████████| 118/118 [00:26<00:00, 4.39it/s]
Test set: Average loss: 0.0220, Accuracy: 9927/10000 (99.27%)
Adjusting learning rate of group 0 to 1.0000e-03.
Epoch 17
Train: Loss=0.0199 Batch_id=117 Accuracy=99.08: 100%|██████████| 118/118 [00:26<00:00, 4.41it/s]
Test set: Average loss: 0.0214, Accuracy: 9925/10000 (99.25%)
Adjusting learning rate of group 0 to 1.0000e-03.
Epoch 18
Train: Loss=0.1040 Batch_id=117 Accuracy=99.10: 100%|██████████| 118/118 [00:27<00:00, 4.30it/s]
Test set: Average loss: 0.0211, Accuracy: 9924/10000 (99.24%)
Adjusting learning rate of group 0 to 1.0000e-03.
Epoch 19
Train: Loss=0.0311 Batch_id=117 Accuracy=99.06: 100%|██████████| 118/118 [00:26<00:00, 4.42it/s]
Test set: Average loss: 0.0209, Accuracy: 9926/10000 (99.26%)
Adjusting learning rate of group 0 to 1.0000e-03.
Epoch 20
Train: Loss=0.0400 Batch_id=117 Accuracy=99.12: 100%|██████████| 118/118 [00:27<00:00, 4.34it/s]
Test set: Average loss: 0.0203, Accuracy: 9930/10000 (99.30%)
Adjusting learning rate of group 0 to 1.0000e-03.
Visualization
Code Description
Folder structure
_____
|___ model.py (contains model description)
|___ utils.py (contains utility functions)
|___ set_device (function to set device as with/without cuda based on availability)
|___ view_data (function to view sample data)
|___ vis_train_test_comp_graphs (function to visualize the train loss/accuracy and test loss/accuracy)
|___ GetCorrectPredCount (function to get correct prediction count)
|___ train (function to train the model)
|___ test (function to test the trained model)