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Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold3

Image Classification
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beit
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Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold3 / README.md
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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_fold3
    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: 0.4291125541125541

Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold3

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: 1.7764
  • Accuracy: 0.4291

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
2.4699 1.0 923 2.4335 0.2140
2.3722 2.0 1846 2.2936 0.2643
2.248 3.0 2769 2.1974 0.2884
2.1383 4.0 3692 2.1137 0.3217
2.0587 5.0 4615 2.0507 0.3404
2.0732 6.0 5538 2.0041 0.3501
2.0202 7.0 6461 1.9644 0.3693
2.0361 8.0 7384 1.9326 0.3764
1.9433 9.0 8307 1.8973 0.3926
1.9102 10.0 9230 1.8743 0.3877
1.9324 11.0 10153 1.8539 0.3950
1.943 12.0 11076 1.8379 0.4061
1.8903 13.0 11999 1.8194 0.4113
1.8833 14.0 12922 1.8092 0.4172
1.8296 15.0 13845 1.8007 0.4205
1.8152 16.0 14768 1.7910 0.4256
2.0261 17.0 15691 1.7844 0.4283
1.8132 18.0 16614 1.7806 0.4283
1.8172 19.0 17537 1.7782 0.4294
1.867 20.0 18460 1.7764 0.4291

Framework versions

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