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metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Boya1_SGD_1-e3_20Epoch_Deit-tiny-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: 0.42384823848238484

Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold4

This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7238
  • Accuracy: 0.4238

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
2.4152 1.0 923 2.4593 0.2073
2.4387 2.0 1846 2.2993 0.2512
2.1969 3.0 2769 2.1607 0.3133
2.0455 4.0 3692 2.0589 0.3320
1.8171 5.0 4615 1.9845 0.3585
1.8796 6.0 5538 1.9302 0.3656
1.8281 7.0 6461 1.8840 0.3816
1.7455 8.0 7384 1.8500 0.3883
1.7072 9.0 8307 1.8232 0.4003
1.7401 10.0 9230 1.8005 0.4046
1.8157 11.0 10153 1.7845 0.4114
1.796 12.0 11076 1.7690 0.4114
1.7335 13.0 11999 1.7588 0.4122
1.6292 14.0 12922 1.7473 0.4190
1.7133 15.0 13845 1.7397 0.4222
1.7521 16.0 14768 1.7345 0.4195
1.8322 17.0 15691 1.7291 0.4244
1.7763 18.0 16614 1.7260 0.4244
1.5996 19.0 17537 1.7248 0.4225
1.6259 20.0 18460 1.7238 0.4238

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.1.0
  • Datasets 2.19.0
  • Tokenizers 0.19.1