36 lines
1.2 KiB
YAML
36 lines
1.2 KiB
YAML
Collections:
|
|
- Name: Shufflenet V2
|
|
Metadata:
|
|
Training Data: ImageNet-1k
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
- No BN decay
|
|
Training Resources: 8x 1080 GPUs
|
|
Epochs: 300
|
|
Batch Size: 1024
|
|
Architecture:
|
|
- Shufflenet V2
|
|
Paper:
|
|
URL: https://openaccess.thecvf.com/content_ECCV_2018/papers/Ningning_Light-weight_CNN_Architecture_ECCV_2018_paper.pdf
|
|
Title: "ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design"
|
|
README: configs/shufflenet_v2/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmpretrain/blob/v0.15.0/mmcls/models/backbones/shufflenet_v2.py#L134
|
|
Version: v0.15.0
|
|
|
|
Models:
|
|
- Name: shufflenet-v2-1x_16xb64_in1k
|
|
Metadata:
|
|
FLOPs: 149000000
|
|
Parameters: 2280000
|
|
In Collection: Shufflenet V2
|
|
Results:
|
|
- Dataset: ImageNet-1k
|
|
Metrics:
|
|
Top 1 Accuracy: 69.55
|
|
Top 5 Accuracy: 88.92
|
|
Task: Image Classification
|
|
Weights: https://download.openmmlab.com/mmclassification/v0/shufflenet_v2/shufflenet_v2_batch1024_imagenet_20200812-5bf4721e.pth
|
|
Config: configs/shufflenet_v2/shufflenet-v2-1x_16xb64_in1k.py
|