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README.md

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+---
+language: en
+license: mit
+library_name: timm
+tags:
+- image-classification
+- resnet50
+- cifar10
+datasets: cifar10
+metrics:
+- accuracy
+model-index:
+- name: resnet50_cifar10
+  results:
+  - task:
+      type: image-classification
+    dataset:
+      name: CIFAR-10
+      type: cifar10
+    metrics:
+    - type: accuracy
+      value: 0.9465
+---
+
+# Model Card for Model ID
+
+This model is a small resnet50 trained on cifar10.
+
+- **Test Accuracy:** 0.9465
+- **License:** MIT
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```python
+import detectors
+import timm
+
+model = timm.create_model("resnet50_cifar10", pretrained=True)
+```
+
+## Training Data
+
+Training data is cifar10.
+
+## Training Hyperparameters
+
+
+- **config**: `scripts/train_configs/cifar10.json`
+
+- **model**: `resnet50_cifar10`
+
+- **dataset**: `cifar10`
+
+- **batch_size**: `128`
+
+- **epochs**: `300`
+
+- **validation_frequency**: `5`
+
+- **seed**: `1`
+
+- **criterion**: `CrossEntropyLoss`
+
+- **criterion_kwargs**: `{}`
+
+- **optimizer**: `SGD`
+
+- **lr**: `0.1`
+
+- **optimizer_kwargs**: `{'momentum': 0.9, 'weight_decay': 0.0005, 'nesterov': 'True'}`
+
+- **scheduler**: `ReduceLROnPlateau`
+
+- **scheduler_kwargs**: `{'factor': 0.1, 'patience': 3, 'threshold': 0.001, 'mode': 'max'}`
+
+- **debug**: `False`
+
+
+## Testing Data
+
+Testing data is cifar10.
+
+---
+
+This model card was created by Eduardo Dadalto.