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resnet-50-mnist-42

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

  • Loss: 0.0867
  • Accuracy: 0.9756

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: 2e-05
  • train_batch_size: 32
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.1104 1.0 1594 0.7291 0.844
0.7721 2.0 3188 0.2278 0.9488
0.648 3.0 4782 0.1525 0.9628
0.5634 4.0 6376 0.1187 0.9684
0.5422 5.0 7970 0.1046 0.9707
0.5031 6.0 9564 0.0981 0.9746
0.4926 7.0 11158 0.0909 0.975
0.4874 8.0 12752 0.0884 0.9751
0.4723 9.0 14346 0.0867 0.9756
0.4628 10.0 15940 0.0868 0.9753

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.1.0
  • Datasets 2.15.0
  • Tokenizers 0.13.3
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Dataset used to train jialicheng/resnet-50-mnist-42

Evaluation results