mmpretrain/configs/mobilenet_v3/metafile.yml

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YAML

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