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README.md

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+---
+language: en
+license: mit
+library_name: timm
+tags:
+- image-classification
+- resnet34
+- svhn
+datasets: svhn
+metrics:
+- accuracy
+model-index:
+- name: resnet34_svhn
+  results:
+  - task:
+      type: image-classification
+    dataset:
+      name: SVHN
+      type: svhn
+    metrics:
+    - type: accuracy
+      value: 0.9626229256299939
+---
+
+# Model Card for Model ID
+
+This model is a small resnet34 trained on svhn.
+
+- **Test Accuracy:** 0.9626229256299939
+- **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("resnet34_svhn", pretrained=True)
+```
+
+## Training Data
+
+Training data is svhn.
+
+## Training Hyperparameters
+
+
+- **config**: `scripts/train_configs/svhn.json`
+
+- **model**: `resnet34_svhn`
+
+- **dataset**: `svhn`
+
+- **batch_size**: `128`
+
+- **epochs**: `300`
+
+- **validation_frequency**: `5`
+
+- **seed**: `1`
+
+- **criterion**: `CrossEntropyLoss`
+
+- **criterion_kwargs**: `{}`
+
+- **optimizer**: `SGD`
+
+- **lr**: `0.01`
+
+- **optimizer_kwargs**: `{'momentum': 0.9, 'weight_decay': 0.0005}`
+
+- **scheduler**: `MultiStepLR`
+
+- **scheduler_kwargs**: `{'gamma': 0.1, 'milestones': [75, 100, 150, 225]}`
+
+- **debug**: `False`
+
+
+## Testing Data
+
+Testing data is svhn.
+
+---
+
+This model card was created by Eduardo Dadalto.