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Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold4

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_fold4
    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: 0.4140921409214092

Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold4

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: 1.7941
  • Accuracy: 0.4141

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
2.4306 1.0 923 2.4407 0.2095
2.409 2.0 1846 2.3053 0.2534
2.2629 3.0 2769 2.2093 0.2808
2.1047 4.0 3692 2.1337 0.3
2.0899 5.0 4615 2.0657 0.3271
2.0152 6.0 5538 2.0140 0.3350
2.1479 7.0 6461 1.9759 0.3439
2.0267 8.0 7384 1.9443 0.3607
2.0062 9.0 8307 1.9180 0.3675
1.9883 10.0 9230 1.8909 0.3770
1.8727 11.0 10153 1.8694 0.3875
1.9236 12.0 11076 1.8511 0.3919
1.9423 13.0 11999 1.8378 0.3981
1.9526 14.0 12922 1.8261 0.3965
1.8178 15.0 13845 1.8139 0.4068
1.9548 16.0 14768 1.8071 0.4041
1.8676 17.0 15691 1.7999 0.4103
1.7727 18.0 16614 1.7976 0.4144
1.7795 19.0 17537 1.7949 0.4141
1.9062 20.0 18460 1.7941 0.4141

Framework versions

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