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README.md
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---
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language: en
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license: mit
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library_name: timm
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tags:
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- image-classification
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- resnet34
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- cifar10
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datasets: cifar10
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metrics:
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- accuracy
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model-index:
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- name: resnet34_simclr_cifar10
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results:
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- task:
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type: image-classification
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dataset:
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name: CIFAR-10
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type: cifar10
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metrics:
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- type: accuracy
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value: 0.8998999999999999
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---
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# Model Card for Model ID
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This model is a small resnet34 trained on cifar10.
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- **Test Accuracy:** 0.8998999999999999
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- **License:** MIT
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## How to Get Started with the Model
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Use the code below to get started with the model.
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```python
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import detectors
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import timm
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model = timm.create_model("resnet34_simclr_cifar10", pretrained=True)
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```
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## Training Data
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Training data is cifar10.
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## Training Hyperparameters
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- **config**: `None`
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- **model**: `resnet34_simclr_cifar10`
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- **batch_size**: `512`
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- **epochs**: `501`
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- **lr**: `0.5`
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- **warmup_epochs**: `10`
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- **validation_frequency**: `50`
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- **output_features_dim**: `128`
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- **seed**: `1`
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- **debug**: `False`
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- **dataset**: `cifar10`
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- **training_mode**: `simclr`
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## Testing Data
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Testing data is cifar10.
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---
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This model card was created by Eduardo Dadalto.
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