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beit-base-patch16-224-pt22k-ft22k-finetuned-mnist

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the mnist dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0202
  • Accuracy: 0.9935

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3376 1.0 937 0.0446 0.9855
0.318 2.0 1874 0.0262 0.9916
0.2374 3.0 2811 0.0202 0.9935

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Dataset used to train Karelito00/beit-base-patch16-224-pt22k-ft22k-finetuned-mnist

Evaluation results