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environments/community/pytorch_optimizer_coding/FOB/README.md
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@ -19,7 +19,7 @@ Instructions on how to write your own task can be found [here](pytorch_fob/tasks
| Name | Dataset | Model | Task | Target Metric | Baseline Score | Baseline Runtime | Hardware |
| ------- | ---- | ----- | ---- | ------------- | -------------- | ---------------- | -------- |
| [mnist](pytorch_fob/tasks/mnist) | MNIST | MLP | Image Classification | Top-1 Accuracy | 0.97 | 1 min | 1 gpu |
| [mnist](baselines/mnist.yaml) | MNIST | MLP | Image Classification | Top-1 Accuracy | 0.97 | 1 min | 1 gpu |
| [classification](pytorch_fob/tasks/classification) | [Imagenet-64x64](https://patrykchrabaszcz.github.io/Imagenet32/) | [Wide ResNet](https://arxiv.org/pdf/1605.07146.pdf) | Image Classification | Top-1 Accuracy | 0.69 | 4h | 4 gpu |
| [classification_small](pytorch_fob/tasks/classification_small) | [CIFAR100](https://www.cs.toronto.edu/~kriz/cifar.html) | [Resnet18](https://arxiv.org/pdf/1512.03385.pdf) | Image Classification | Top-1 Accuracy | 0.77 | 10 min | 1 gpu |
| [segmentation](pytorch_fob/tasks/segmentation) | [MIT Scene Parse](http://sceneparsing.csail.mit.edu/) | [SegFormer](https://arxiv.org/abs/2105.15203) | Semantic Segmentation | Intersection over Union (IoU) | 35.6 | 5h | 4 gpu |