Model card for resnet18

A ResNet-B image classification model.

This model features:

• ReLU activations
• Single layer 7x7 convolution with pooling
• 1x1 convolution shortcut downsample

Trained on ImageNet-1k in timm using recipe template described below.

Recipe details:

• ResNet Strikes Back A1 recipe
• LAMB optimizer with BCE loss
• Cosine LR schedule with warmup

Model Details

• Model Type: Image classification / feature backbone
• Model Stats:
  • Params (M): 11.7
  • GMACs: 1.8
  • Activations (M): 2.5
  • Image size: train = 224 x 224, test = 288 x 288
• Papers:
  • ResNet strikes back: An improved training procedure in timm: https://arxiv.org/abs/2110.00476
  • Deep Residual Learning for Image Recognition: https://arxiv.org/abs/1512.03385