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---
library_name: keras, image classification
---
## 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/
## Intended uses & limitations
The trained model can be used as a learned representation for downstream tasks like image classification.
## Training and evaluation data
Original Cifar 10 train & test dataset were loaded from tensorflow datasets.
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>
</details> |