Image Classification on Generic Image Dataset 224x224
86.26Peak Training Memory (MB)Inference
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| InferenceBackbone=ViT2025.10 | 86.26 | — | |
| Fisher InformationBackbone=ViT2025.10 | 86.27 | 386.6 | |
| Transfer LearningBackbone=ViT2025.10 | 86.46 | — | |
| AdaBetBackbone=ViT2025.10 | 93.64 | 86.26 | |
| Last-K LayersBackbone=ViT2025.10 | 103.1 | — | |
| ElasticTrainerBackbone=ViT2025.10 | 138.05 | 386.6 | |
| InferenceBackbone=ResNet502025.10 | 243.04 | — | |
| Transfer LearningBackbone=ResNet502025.10 | 243.3 | — | |
| AdaBetBackbone=ResNet502025.10 | 261.78 | 243.04 | |
| Last-K LayersBackbone=ResNet502025.10 | 263.19 | — | |
| Fisher InformationBackbone=ResNet502025.10 | 270.98 | 777.12 | |
| ElasticTrainerBackbone=ResNet502025.10 | 299.66 | 777.12 | |
| InferenceBackbone=MobileNetV22025.10 | 315.86 | — | |
| Transfer LearningBackbone=MobileNetV22025.10 | 316.02 | — | |
| Fisher InformationBackbone=MobileNetV22025.10 | 316.02 | 373.58 | |
| AdaBetBackbone=MobileNetV22025.10 | 318.5 | 315.86 | |
| Last-K LayersBackbone=MobileNetV22025.10 | 319.46 | — | |
| ElasticTrainerBackbone=MobileNetV22025.10 | 322.13 | 373.58 | |
| Full TrainingBackbone=MobileNetV22025.10 | 373.58 | — | |
| PruneTrainBackbone=MobileNetV22025.10 | 373.58 | 373.58 | |
| Full TrainingBackbone=ViT2025.10 | 386.6 | — | |
| PruneTrainBackbone=ViT2025.10 | 386.6 | 386.6 | |
| Full TrainingBackbone=ResNet502025.10 | 777.12 | — | |
| PruneTrainBackbone=ResNet502025.10 | 777.12 | 777.12 | |
| InferenceBackbone=VGG162025.10 | 932.21 | — | |
| Transfer LearningBackbone=VGG162025.10 | 932.27 | — | |
| Fisher InformationBackbone=VGG162025.10 | 932.28 | 988.77 | |
| Last-K LayersBackbone=VGG162025.10 | 932.41 | — | |
| AdaBetBackbone=VGG162025.10 | 932.45 | 932.21 | |
| ElasticTrainerBackbone=VGG162025.10 | 969.44 | 988.77 | |
| Full TrainingBackbone=VGG162025.10 | 988.77 | — | |
| PruneTrainBackbone=VGG162025.10 | 988.77 | 988.77 |