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---
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. |