| image-classification-on-imagenet | SparK (ConvNeXt-Large, 384) | #178 | Top 1 Accuracy: 86.0%Number of params: 198M |
| instance-segmentation-on-coco-2017-val | SparK (ConvNeXt V1-B Mask R-CNN) | #1 | mask AP*: 45.1mask AP: 45.1AP: 45.1 |
| self-supervised-image-classification-on-1 | SparK (ConvNeXt-Large, 384) | #18 | Top 1 Accuracy: 86.0%Number of Params: 198M |
| self-supervised-image-classification-on-1 | SparK (ConvNeXt-Large) | #24 | Top 1 Accuracy: 85.4%Number of Params: 198M |
| self-supervised-image-classification-on-1 | ConvNeXt-Base (SparK pre-training) | #27 | Top 1 Accuracy: 84.8%Number of Params: 89M |
| self-supervised-image-classification-on-1 | ConvNeXt-Small (SparK pre-training) | #37 | Top 1 Accuracy: 84.1%Number of Params: 50M |
| self-supervised-image-classification-on-1 | ResNet-200 (SparK pre-training) | #47 | Top 1 Accuracy: 83.1%Number of Params: 65M |
| self-supervised-image-classification-on-1 | ResNet-152 (SparK pre-training) | #49 | Top 1 Accuracy: 82.7%Number of Params: 60M |
| self-supervised-image-classification-on-1 | ResNet-101 (SparK pre-training) | #53 | Top 1 Accuracy: 82.2%Number of Params: 44M |
| self-supervised-image-classification-on-1 | ResNet-50 (SparK pre-training) | #55 | Top 1 Accuracy: 80.6%Number of Params: 26M |