
# 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.
{"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}]}]}]}
timm pytorch image-classification resnet34 svhn en dataset:svhn license:mit model-index region:us
TAGS
#timm #pytorch #image-classification #resnet34 #svhn #en #dataset-svhn #license-mit #model-index #region-us 


# 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.



## Training Data

Training data is svhn.

## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- 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.
# 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. ## Training Data

Training data is svhn. ## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- 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.
TAGS
#timm #pytorch #image-classification #resnet34 #svhn #en #dataset-svhn #license-mit #model-index #region-us 
 # 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. ## Training Data

Training data is svhn. ## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- 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.
TAGS
#timm #pytorch #image-classification #resnet34 #svhn #en #dataset-svhn #license-mit #model-index #region-us 
# 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.## Training Data

Training data is svhn.## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- 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.