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Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold2

Image Classification
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beit
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metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.41702702702702704

Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold2

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

  • Loss: 1.8092
  • Accuracy: 0.4170

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: 0.001
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.364 1.0 923 2.4299 0.2108
2.3719 2.0 1846 2.2817 0.2649
2.2408 3.0 2769 2.1860 0.2889
2.1829 4.0 3692 2.1102 0.3143
2.0369 5.0 4615 2.0577 0.3241
2.061 6.0 5538 2.0066 0.3419
1.9167 7.0 6461 1.9797 0.3568
2.0057 8.0 7384 1.9411 0.3673
2.0098 9.0 8307 1.9258 0.3722
1.9046 10.0 9230 1.9019 0.3822
1.862 11.0 10153 1.8785 0.3922
1.8051 12.0 11076 1.8624 0.3973
1.8752 13.0 11999 1.8478 0.3981
1.9831 14.0 12922 1.8389 0.4032
1.8913 15.0 13845 1.8338 0.4051
1.9373 16.0 14768 1.8269 0.4086
1.8457 17.0 15691 1.8202 0.4089
1.7936 18.0 16614 1.8117 0.4159
1.7608 19.0 17537 1.8101 0.4168
1.9672 20.0 18460 1.8092 0.4170

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0
  • Datasets 2.14.6
  • Tokenizers 0.14.1