resnet34_cifar100 / README.md
edadaltocg's picture
Upload README.md with huggingface_hub
997f1cc
---
language: en
license: mit
library_name: timm
tags:
- image-classification
- resnet34
- cifar100
datasets: cifar100
metrics:
- accuracy
model-index:
- name: resnet34_cifar100
results:
- task:
type: image-classification
dataset:
name: CIFAR-100
type: cifar100
metrics:
- type: accuracy
value: 0.7978
---
# Model Card for Model ID
This model is a small resnet34 trained on cifar100.
- **Test Accuracy:** 0.7978
- **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_cifar100", pretrained=True)
```
## Training Data
Training data is cifar100.
## Training Hyperparameters
- **config**: `scripts/train_configs/cifar100.json`
- **model**: `resnet34_cifar100`
- **dataset**: `cifar100`
- **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}`
- **scheduler**: `CosineAnnealingLR`
- **scheduler_kwargs**: `{'T_max': 280}`
- **debug**: `False`
## Testing Data
Testing data is cifar100.
---
This model card was created by Eduardo Dadalto.