27 lines
1.4 KiB
Markdown
27 lines
1.4 KiB
Markdown
= Timeline of Progress =
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== Tuesday, February 27th, 2024 ==
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- Determined that lack of effectiveness for low values of epsilon for the FGSM attack is normal ([[https://pytorch.org/tutorials/beginner/fgsm_tutorial.html#accuracy-vs-epsilon|PyTorch Example Results]]).
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- Finished trainable, saveable MNIST model
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- Working on manipulating the MNIST dataset for cross validation and filtering
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- Looking into implementing [[https://www.cs.toronto.edu/~kriz/cifar.html|CIFAR-10]] due to the model architecture and the nature of the images being classified
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== Thursday, February 29th, 2024 ==
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- Created functionality for Kuwahara filtering of batches of 64 images at runtime
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- Encountering crash in last batch
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== Monday, March 4th, 2024 ==
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- Last batch of epoch doesn't have 64 images, batch size now variable
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- Encountered crash when testing at end of epoch
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- Fixed crash, testing required specifying batch size
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- All 14 epochs train successfully on filtered data
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- Added `--filter` option to enable filtering on training and test data
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- Encountered crash, `args` not passed to `test` function
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- `args` variable now passed to `test` function
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- Filtered and unfiltered models saved to different files
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- Tested filtered model with FGSM attack
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- Got results inline with unfiltered model
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- Realized that I forgot to save the filtered model
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- Tested actually filtered model with FGSM attack
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- Got really good results inline with hypothesis
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