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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - cats_vs_dogs
metrics:
  - accuracy
model-index:
  - name: cat_vs_dog_classifier
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: cats_vs_dogs
          type: cats_vs_dogs
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9857610707674783

cat_vs_dog_classifier

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0341
  • Accuracy: 0.9858

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 257 0.0387 0.9855
0.0329 2.0 514 0.0302 0.9885

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2