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metadata
language: en
license: mit
library_name: timm
tags:
  - image-classification
  - resnet50
  - cifar100
datasets: cifar100
metrics:
  - accuracy
model-index:
  - name: resnet50_supcon_cifar100
    results:
      - task:
          type: image-classification
        dataset:
          name: CIFAR-100
          type: cifar100
        metrics:
          - type: accuracy
            value: 0.6854

Model Card for resnet50_supcon_cifar100

This model is a small resnet50 trained on cifar100.

  • Test Accuracy: 0.6854
  • 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("resnet50_supcon_cifar100", pretrained=True)

Training Data

Training data is cifar100.

Training Hyperparameters

  • config: None

  • model: resnet50_supcon_cifar100

  • batch_size: 512

  • epochs: 501

  • lr: 0.5

  • warmup_epochs: 10

  • validation_frequency: 50

  • output_features_dim: 128

  • seed: 1

  • debug: False

  • dataset: cifar100

  • training_mode: supcon

Testing Data

Testing data is cifar100.


This model card was created by Eduardo Dadalto.