Collections: - Name: MobileNet V3 Metadata: Training Data: ImageNet-1k Training Techniques: - RMSprop with Momentum - Weight Decay Training Resources: 8x V100 GPUs Epochs: 600 Batch Size: 1024 Architecture: - MobileNet V3 Paper: URL: https://arxiv.org/abs/1905.02244 Title: Searching for MobileNetV3 README: configs/mobilenet_v3/README.md Code: URL: https://github.com/open-mmlab/mmpretrain/blob/v0.15.0/mmcls/models/backbones/mobilenet_v3.py Version: v0.15.0 Models: - Name: mobilenet-v3-small-050_3rdparty_in1k Metadata: FLOPs: 24895000 Parameters: 1590000 In Collection: MobileNet V3 Results: - Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 57.91 Top 5 Accuracy: 80.19 Task: Image Classification Weights: https://download.openmmlab.com/mmclassification/v0/mobilenet_v3/mobilenet-v3-small-050_3rdparty_in1k_20221114-e0b86be1.pth Config: configs/mobilenet_v3/mobilenet-v3-small-050_8xb128_in1k.py Converted From: Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv3_small_050_lambc-4b7bbe87.pth Code: https://github.com/rwightman/pytorch-image-models/blob/main/timm/models/mobilenetv3.py - Name: mobilenet-v3-small-075_3rdparty_in1k Metadata: FLOPs: 44791000 Parameters: 2040000 In Collection: MobileNet V3 Results: - Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 65.23 Top 5 Accuracy: 85.44 Task: Image Classification Weights: https://download.openmmlab.com/mmclassification/v0/mobilenet_v3/mobilenet-v3-small-075_3rdparty_in1k_20221114-2011fa76.pth Config: configs/mobilenet_v3/mobilenet-v3-small-075_8xb128_in1k.py Converted From: Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv3_small_075_lambc-384766db.pth Code: https://github.com/rwightman/pytorch-image-models/blob/main/timm/models/mobilenetv3.py - Name: mobilenet-v3-small_8xb128_in1k Metadata: FLOPs: 60000000 Parameters: 2540000 In Collection: MobileNet V3 Results: - Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 66.68 Top 5 Accuracy: 86.74 Task: Image Classification Weights: https://download.openmmlab.com/mmclassification/v0/mobilenet_v3/mobilenet-v3-small_8xb128_in1k_20221114-bd1bfcde.pth Config: configs/mobilenet_v3/mobilenet-v3-small_8xb128_in1k.py - Name: mobilenet-v3-small_3rdparty_in1k Metadata: FLOPs: 60000000 Parameters: 2540000 In Collection: MobileNet V3 Results: - Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 67.66 Top 5 Accuracy: 87.41 Task: Image Classification Weights: https://download.openmmlab.com/mmclassification/v0/mobilenet_v3/convert/mobilenet_v3_small-8427ecf0.pth Config: configs/mobilenet_v3/mobilenet-v3-small_8xb128_in1k.py Converted From: Weights: https://download.pytorch.org/models/mobilenet_v3_small-047dcff4.pth Code: https://github.com/pytorch/vision/blob/main/torchvision/models/mobilenetv3.py - Name: mobilenet-v3-large_8xb128_in1k Metadata: FLOPs: 230000000 Parameters: 5480000 In Collection: MobileNet V3 Results: - Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 73.49 Top 5 Accuracy: 91.31 Task: Image Classification Weights: https://download.openmmlab.com/mmclassification/v0/mobilenet_v3/mobilenet-v3-large_8xb128_in1k_20221114-0ed9ed9a.pth Config: configs/mobilenet_v3/mobilenet-v3-large_8xb128_in1k.py - Name: mobilenet-v3-large_3rdparty_in1k Metadata: FLOPs: 230000000 Parameters: 5480000 In Collection: MobileNet V3 Results: - Dataset: ImageNet-1k Metrics: Top 1 Accuracy: 74.04 Top 5 Accuracy: 91.34 Task: Image Classification Weights: https://download.openmmlab.com/mmclassification/v0/mobilenet_v3/convert/mobilenet_v3_large-3ea3c186.pth Config: configs/mobilenet_v3/mobilenet-v3-large_8xb128_in1k.py Converted From: Weights: https://download.pytorch.org/models/mobilenet_v3_large-8738ca79.pth Code: https://github.com/pytorch/vision/blob/main/torchvision/models/mobilenetv3.py