Collections: - Name: SimMIM Metadata: Training Data: ImageNet-1k Training Techniques: - AdamW Training Resources: 16x A100 GPUs Architecture: - Swin Paper: Title: 'SimMIM: A Simple Framework for Masked Image Modeling' URL: https://arxiv.org/abs/2111.09886 README: configs/simmim/README.md Models: - Name: simmim_swin-base-w6_8xb256-amp-coslr-100e_in1k-192px Metadata: Epochs: 100 Batch Size: 2048 FLOPs: 18832161792 Parameters: 89874104 Training Data: ImageNet-1k In Collection: SimMIM Results: null Weights: https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192_20220829-0e15782d.pth Config: configs/simmim/simmim_swin-base-w6_8xb256-amp-coslr-100e_in1k-192px.py Downstream: - swin-base-w6_simmim-100e-pre_8xb256-coslr-100e_in1k-192px - swin-base-w7_simmim-100e-pre_8xb256-coslr-100e_in1k - Name: simmim_swin-base-w6_16xb128-amp-coslr-800e_in1k-192px Metadata: Epochs: 100 Batch Size: 2048 FLOPs: 18832161792 Parameters: 89874104 Training Data: ImageNet-1k In Collection: SimMIM Results: null Weights: https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192_20220916-a0e931ac.pth Config: configs/simmim/simmim_swin-base-w6_16xb128-amp-coslr-800e_in1k-192px.py Downstream: - swin-base-w6_simmim-800e-pre_8xb256-coslr-100e_in1k-192px - Name: simmim_swin-large-w12_16xb128-amp-coslr-800e_in1k-192px Metadata: Epochs: 100 Batch Size: 2048 FLOPs: 55849130496 Parameters: 199920372 Training Data: ImageNet-1k In Collection: SimMIM Results: null Weights: https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192_20220916-4ad216d3.pth Config: configs/simmim/simmim_swin-large-w12_16xb128-amp-coslr-800e_in1k-192px.py Downstream: - swin-large-w14_simmim-800e-pre_8xb256-coslr-100e_in1k - Name: swin-base-w6_simmim-100e-pre_8xb256-coslr-100e_in1k-192px Metadata: Epochs: 100 Batch Size: 2048 FLOPs: 11303976960 Parameters: 87750176 Training Data: ImageNet-1k In Collection: SimMIM Results: - Task: Image Classification Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 82.7 Weights: https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_8xb256-amp-coslr-100e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k/swin-base_ft-8xb256-coslr-100e_in1k_20220829-9cf23aa1.pth Config: configs/simmim/benchmarks/swin-base-w6_8xb256-coslr-100e_in1k-192px.py - Name: swin-base-w7_simmim-100e-pre_8xb256-coslr-100e_in1k Metadata: Epochs: 100 Batch Size: 2048 FLOPs: 15466852352 Parameters: 87768224 Training Data: ImageNet-1k In Collection: SimMIM Results: - Task: Image Classification Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 83.5 Weights: null Config: configs/simmim/benchmarks/swin-base-w7_8xb256-coslr-100e_in1k.py - Name: swin-base-w6_simmim-800e-pre_8xb256-coslr-100e_in1k-192px Metadata: Epochs: 100 Batch Size: 2048 FLOPs: 15466852352 Parameters: 87768224 Training Data: ImageNet-1k In Collection: SimMIM Results: - Task: Image Classification Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 83.8 Weights: https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-base_16xb128-amp-coslr-800e_in1k-192/swin-base_ft-8xb256-coslr-100e_in1k-224/swin-base_ft-8xb256-coslr-100e_in1k-224_20221208-155cc6e6.pth Config: configs/simmim/benchmarks/swin-base-w7_8xb256-coslr-100e_in1k.py - Name: swin-large-w14_simmim-800e-pre_8xb256-coslr-100e_in1k Metadata: Epochs: 100 Batch Size: 2048 FLOPs: 38853083136 Parameters: 196848316 Training Data: ImageNet-1k In Collection: SimMIM Results: - Task: Image Classification Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 84.8 Weights: https://download.openmmlab.com/mmselfsup/1.x/simmim/simmim_swin-large_16xb128-amp-coslr-800e_in1k-192/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224/swin-large_ft-8xb256-coslr-ws14-100e_in1k-224_20220916-d4865790.pth Config: configs/simmim/benchmarks/swin-large-w14_8xb256-coslr-100e_in1k.py