---
tags:
- image-classification
- timm
library_tag: timm
license: apache-2.0
datasets:
- imagenet-1k
- imagenet-12k
---
# Model card for convnext_small.in12k_ft_in1k_384

A ConvNeXt image classification model. Pretrained in `timm` on ImageNet-12k (a 11821 class subset of full ImageNet-22k) and fine-tuned on ImageNet-1k by Ross Wightman.

ImageNet-12k training done on TPUs thanks to support of the [TRC](https://sites.research.google/trc/about/) program.

Fine-tuning performed on 8x GPU [Lambda Labs](https://lambdalabs.com/) cloud instances.


## Model Details
- **Model Type:** Image classification / feature backbone
- **Model Stats:**
  - Params (M): 50.2
  - GMACs: 25.6
  - Activations (M): 63.4
  - Image size: 384 x 384
- **Dataset:** ImageNet-1k
- **Pretrain Dataset:** ImageNet-12k
- **Papers:**
  - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545

## Citation
```
@misc{rw2019timm,
  author = {Ross Wightman},
  title = {PyTorch Image Models},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  doi = {10.5281/zenodo.4414861},
  howpublished = {\url{https://github.com/rwightman/pytorch-image-models}}
}
```
```
@article{liu2022convnet,
  author  = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
  title   = {A ConvNet for the 2020s},
  journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year    = {2022},
}        
```