pokemon_class_model / README.md
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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - pokemon-classification
metrics:
  - accuracy
model-index:
  - name: pokemon_class_model
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: pokemon-classification
          type: pokemon-classification
          config: full
          split: train
          args: full
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8439425051334702

pokemon_class_model

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

  • Loss: 2.7799
  • Accuracy: 0.8439

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
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
4.871 1.0 61 4.8286 0.1129
4.4362 2.0 122 4.3949 0.5626
3.9543 3.0 183 3.9551 0.7238
3.5859 4.0 244 3.6081 0.7772
3.2793 5.0 305 3.3454 0.8049
3.0146 6.0 366 3.1411 0.8152
2.8492 7.0 427 2.9854 0.8347
2.6706 8.0 488 2.8625 0.8501
2.5676 9.0 549 2.8014 0.8337
2.6059 10.0 610 2.7799 0.8439

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0