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Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold3

Image Classification
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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_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: 0.42884199134199136

Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold3

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: 1.7155
  • Accuracy: 0.4288

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
2.4106 1.0 923 2.4578 0.2002
2.3587 2.0 1846 2.2972 0.2516
2.1274 3.0 2769 2.1627 0.3055
2.1583 4.0 3692 2.0604 0.3279
1.9036 5.0 4615 1.9842 0.3458
1.7721 6.0 5538 1.9243 0.3582
1.9867 7.0 6461 1.8782 0.3726
1.8532 8.0 7384 1.8428 0.3891
1.8503 9.0 8307 1.8165 0.4004
1.79 10.0 9230 1.7943 0.4037
1.7717 11.0 10153 1.7761 0.4091
1.7696 12.0 11076 1.7613 0.4148
1.7298 13.0 11999 1.7507 0.4191
1.7468 14.0 12922 1.7401 0.4210
1.6085 15.0 13845 1.7322 0.4229
1.7188 16.0 14768 1.7257 0.4278
1.7307 17.0 15691 1.7212 0.4259
1.5257 18.0 16614 1.7177 0.4275
1.6729 19.0 17537 1.7160 0.4294
1.7293 20.0 18460 1.7155 0.4288

Framework versions

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