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SimSiam
keras-io/SimSiam
SimSiam is a image classification model from keras-io. Use it when you need a label for an image. It is set up for tf-keras.
This repo contains the trained model Self-supervised contrastive learning with SimSiam on CIFAR-10 Dataset. Keras link: https://keras.io/examples/vision/simsiam/
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At a glance
- Task
- Image Classification
- Library
- tf-keras
- Access
- Public
- Created
- Jun 14, 2022
- Updated
- Jul 5, 2024
- SHA
- fb91e688
Model card
From the Hugging Face model README
Model description
This repo contains the trained model Self-supervised contrastive learning with SimSiam on CIFAR-10 Dataset. Keras link: https://keras.io/examples/vision/simsiam/
Full credits to https://twitter.com/RisingSayak
Intended uses & limitations
The trained model can be used as a learned representation for downstream tasks like image classification.
Training and evaluation data
The dataset we are using here is called CIFAR-100. The CIFAR-10 dataset consists of 60000 32x32 color images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
Two particular augmentation transforms that seem to matter the most are:
- Random resized crops
- Color distortions
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
| name | learning_rate | decay | momentum | nesterov | training_precision |
|---|---|---|---|---|---|
| SGD | {'class_name': 'CosineDecay', 'config': {'initial_learning_rate': 0.03, 'decay_steps': 3900, 'alpha': 0.0, 'name': None}} | 0.0 | 0.8999999761581421 | False | float32 |
Model Plot
<details> <summary>View Model Plot</summary>
- Task
- Image Classification
- Library
- tf-keras
- Created
- Jun 14, 2022
- Updated
- Jul 5, 2024