
# Model Card for Model ID

This model is a small resnet18 trained on cifar10.

- **Test Accuracy:** 0.9498
- **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("resnet18_cifar10", pretrained=True)
```

## Training Data

Training data is cifar10.

## Training Hyperparameters


- **config**: `scripts/train_configs/cifar10.json`

- **model**: `resnet18_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.
{"language": "en", "license": "mit", "library_name": "timm", "tags": ["image-classification", "resnet18", "cifar10"], "datasets": "cifar10", "metrics": ["accuracy"], "model-index": [{"name": "resnet18_cifar10", "results": [{"task": {"type": "image-classification"}, "dataset": {"name": "CIFAR-10", "type": "cifar10"}, "metrics": [{"type": "accuracy", "value": 0.9498}]}]}]}
timm pytorch image-classification resnet18 cifar10 en dataset:cifar10 license:mit model-index region:us
TAGS
#timm #pytorch #image-classification #resnet18 #cifar10 #en #dataset-cifar10 #license-mit #model-index #region-us 


# Model Card for Model ID

This model is a small resnet18 trained on cifar10.

- Test Accuracy: 0.9498
- License: MIT

## How to Get Started with the Model

Use the code below to get started with the model.



## Training Data

Training data is cifar10.

## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- model: 'resnet18_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.
# Model Card for Model ID

This model is a small resnet18 trained on cifar10.

- Test Accuracy: 0.9498
- License: MIT ## How to Get Started with the Model

Use the code below to get started with the model. ## Training Data

Training data is cifar10. ## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- model: 'resnet18_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.
TAGS
#timm #pytorch #image-classification #resnet18 #cifar10 #en #dataset-cifar10 #license-mit #model-index #region-us 
 # Model Card for Model ID

This model is a small resnet18 trained on cifar10.

- Test Accuracy: 0.9498
- License: MIT ## How to Get Started with the Model

Use the code below to get started with the model. ## Training Data

Training data is cifar10. ## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- model: 'resnet18_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.
TAGS
#timm #pytorch #image-classification #resnet18 #cifar10 #en #dataset-cifar10 #license-mit #model-index #region-us 
# Model Card for Model ID

This model is a small resnet18 trained on cifar10.

- Test Accuracy: 0.9498
- License: MIT## How to Get Started with the Model

Use the code below to get started with the model.## Training Data

Training data is cifar10.## Training Hyperparameters


- config: 'scripts/train_configs/URL'

- model: 'resnet18_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.