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This model is a small vgg16_bn trained on cifar100.

  • Test Accuracy: 0.7494
  • License: MIT

How to Get Started with the Model

Use the code below to get started with the model.

import detectors
import timm

model = timm.create_model("vgg16_bn_cifar100", pretrained=True)

Training Data

Training data is cifar100.

Training Hyperparameters

  • config: scripts/train_configs/cifar100.json

  • model: vgg16_bn_cifar100

  • dataset: cifar100

  • batch_size: 128

  • epochs: 300

  • validation_frequency: 5

  • seed: 1

  • criterion: CrossEntropyLoss

  • criterion_kwargs: {}

  • optimizer: SGD

  • lr: 0.1

  • optimizer_kwargs: {'momentum': 0.9, 'weight_decay': 0.0005}

  • scheduler: CosineAnnealingLR

  • scheduler_kwargs: {'T_max': 280}

  • debug: False

Testing Data

Testing data is cifar100.

This model card was created by Eduardo Dadalto.

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Dataset used to train edadaltocg/vgg16_bn_cifar100

Evaluation results