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metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: results
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train[80%:]
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.0625

results

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

  • Loss: 4.5590
  • Accuracy: 0.0625

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: 5e-05
  • 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
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.6612 1.0 40 3.9513 0.0
0.8129 2.0 80 3.9721 0.025
0.3799 3.0 120 4.3376 0.0125
0.0946 4.0 160 4.4142 0.0563
0.019 5.0 200 4.5590 0.0625
0.0062 6.0 240 4.9286 0.0437
0.0039 7.0 280 5.0577 0.0437
0.0028 8.0 320 5.1624 0.0437
0.0024 9.0 360 5.2316 0.0437
0.0023 10.0 400 5.2923 0.0437
0.0019 11.0 440 5.3317 0.0375
0.0017 12.0 480 5.3658 0.0375
0.0016 13.0 520 5.3915 0.0375
0.0016 14.0 560 5.4004 0.0375
0.0016 15.0 600 5.4022 0.0375

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1