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resnet-50-cifar10-quality-drift

This model is a fine-tuned version of microsoft/resnet-50 on the cifar10_quality_drift dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8235
  • Accuracy: 0.724
  • F1: 0.7222

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
1.7311 1.0 750 1.1310 0.6333 0.6300
1.1728 2.0 1500 0.8495 0.7153 0.7155
1.0322 3.0 2250 0.8235 0.724 0.7222

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Evaluation results