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---
language: en
license: mit
library_name: timm
tags:
- image-classification
- timm/vit_base_patch16_224.orig_in21k_ft_in1k
- cifar10
datasets: cifar10
metrics:
- accuracy
model-index:
- name: vit_base_patch16_224_in21k_ft_cifar10
results:
- task:
type: image-classification
dataset:
name: CIFAR-10
type: cifar10
metrics:
- type: accuracy
value: 0.9896
---
# Model Card for Model ID
This model is a small timm/vit_base_patch16_224.orig_in21k_ft_in1k trained on cifar10.
- **Test Accuracy:** 0.9896
- **License:** MIT
## How to Get Started with the Model
Use the code below to get started with the model.
```python
import timm
import torch
from torch import nn
model = timm.create_model("timm/vit_base_patch16_224.orig_in21k_ft_in1k", pretrained=False)
model.head = nn.Linear(model.head.in_features, 10)
model.load_state_dict(
torch.hub.load_state_dict_from_url(
"https://huggingface.co/edadaltocg/vit_base_patch16_224_in21k_ft_cifar10/resolve/main/pytorch_model.bin",
map_location="cpu",
file_name="vit_base_patch16_224_in21k_ft_cifar10.pth",
)
)
```
## Training Data
Training data is cifar10.
## Training Hyperparameters
- **config**: `scripts/train_configs/ft_cifar10.json`
- **model**: `vit_base_patch16_224_in21k_ft_cifar10`
- **dataset**: `cifar10`
- **batch_size**: `64`
- **epochs**: `10`
- **validation_frequency**: `1`
- **seed**: `1`
- **criterion**: `CrossEntropyLoss`
- **criterion_kwargs**: `{}`
- **optimizer**: `SGD`
- **lr**: `0.01`
- **optimizer_kwargs**: `{'momentum': 0.9, 'weight_decay': 0.0}`
- **scheduler**: `CosineAnnealingLR`
- **scheduler_kwargs**: `{'T_max': 10}`
- **debug**: `False`
## Testing Data
Testing data is cifar10.
---
This model card was created by Eduardo Dadalto. |