Collections:
  - Name: FP16
    Metadata:
      Training Data: ImageNet
      Training Resources: 8x V100 GPUs
      Training Techniques:
        - SGD with Momentum
        - Weight Decay
        - Mixed Precision Training
    Paper: https://arxiv.org/abs/1710.03740
    README: configs/fp16/README.md

Models:
- Config: configs/fp16/resnet50_b32x8_fp16_dynamic_imagenet.py
  In Collection: FP16
  Metadata:
    FLOPs: 4120000000
    Parameters: 25560000
    Epochs: 100
    Batch Size: 256
    Architecture:
      - ResNet
  Name: resnet50_b32x8_fp16_dynamic_imagenet
  Results:
  - Dataset: ImageNet
    Metrics:
      Top 1 Accuracy: 76.32
      Top 5 Accuracy: 93.04
    Task: Image Classification
  Weights: https://download.openmmlab.com/mmclassification/v0/fp16/resnet50_batch256_fp16_imagenet_20210320-b3964210.pth