metadata

library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - image-classification
  - vision
  - generated_from_trainer
datasets:
  - arrow
metrics:
  - accuracy
model-index:
  - name: tcg-magic-classifier
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: acidtib/tcg-magic-cards
          type: arrow
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.25452380952380954

tcg-magic-classifier

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

Loss: 7.9836
Accuracy: 0.2545

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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 420
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
8.3148	1.0	488	8.2632	0.0055
8.1958	2.0	976	8.1519	0.0598
8.089	3.0	1464	8.0596	0.1567
8.0208	4.0	1952	8.0033	0.2276
7.983	5.0	2440	7.9836	0.2545

Framework versions

Transformers 4.46.0.dev0
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1