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Final model as a result of graduation work
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@kiteiru kiteiru released this 05 Jul 18:22
· 66 commits to main since this release
v1.0.0
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Learn about vigilant mode.

This model was achieved after series of experiments.
Model is described with its parts and training hyperparameters (for reproducing results also need to mention images and augmentation parameters), namely:

Architecture: Unet
Encoder/backbone: EffecientNet-b4
Loss: BinaryCrossEntropy
Optimizer: RMSProp(lr = 8.57e-4, eps = 8.14e-6, mu = 0.479)
Batchsize: 8
Cropsize: 384 px
Augmentation: HorizontalFlip(probability = 0.736), VerticalFlip(probability = 0.277), Rotate(limit=30, probability = 0.735), ColorJitter(brightness=0.2, contrast=0.2, saturation=0.2, hue=0.2, probability = 0.703)
Markup: Circles and Ellipses separately

This models are trained, validated and tested on data organization "equal" due to the higher variability of data in sets in comparison with "certain" and "random" data organizations.

Assets 3
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