---
language: en
license: mit
library_name: timm
tags:
- image-classification
- resnet18
- cifar100
datasets: cifar100
metrics:
- accuracy
model-index:
- name: resnet18_cifar100
  results:
  - task:
      type: image-classification
    dataset:
      name: CIFAR-100
      type: cifar100
    metrics:
    - type: accuracy
      value: 0.7843
---

# Model Card for Model ID

This model is a small resnet18 trained on cifar100.

- **Test Accuracy:** 0.7843
- **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_cifar100", pretrained=True)
```

## Training Data

Training data is cifar100.

## Training Hyperparameters


- config: scripts/train_configs/cifar100.json

- model: resnet18_cifar100

- dataset: cifar100

- batch_size: 64

- epochs: 200

- validation_frequency: 5

- seed: 1

- criterion: CrossEntropyLoss

- criterion_kwargs: {}

- optimizer: SGD

- lr: 0.1

- optimizer_kwargs: {'momentum': 0.9, 'weight_decay': 0.0005}

- scheduler: CosineAnnealingLR

- scheduler_kwargs: {'T_max': 190}

- debug: False


## Testing Data

Testing data is cifar100.

This model card was created by Eduardo Dadalto.