---
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. It achieves the following results on the evaluation set: Accuracy: 0.7843.

- **Developed by:** Eduardo Dadalto
- **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

<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

Training data is cifar100.

## Training Hyperparameters

## Evaluation

### Testing Data

<!-- This should link to a Data Card if possible. -->

Testing data is cifar100.

## Results

Accuracy is 0.7843.