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# finetuned-cards-blackjack

This model is a fine-tuned version of [google/vit-base-patch16-224-in21K](https://huggingface.co/google/vit-base-patch16-224-in21K) on the card_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5081
- Accuracy: 0.8696

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3563        | 0.24  | 100  | 1.1495          | 0.6750   |
| 1.3393        | 0.48  | 200  | 1.0388          | 0.7204   |
| 1.2033        | 0.73  | 300  | 0.9324          | 0.7547   |
| 0.9672        | 0.97  | 400  | 0.8558          | 0.7659   |
| 0.8674        | 1.21  | 500  | 0.8456          | 0.7616   |
| 0.8277        | 1.45  | 600  | 0.7563          | 0.7959   |
| 0.8703        | 1.69  | 700  | 0.8465          | 0.7539   |
| 0.893         | 1.94  | 800  | 0.6881          | 0.8002   |
| 0.9454        | 2.18  | 900  | 0.7211          | 0.8027   |
| 0.8109        | 2.42  | 1000 | 0.6369          | 0.8285   |
| 0.8762        | 2.66  | 1100 | 0.6336          | 0.8396   |
| 0.8034        | 2.91  | 1200 | 0.6580          | 0.8165   |
| 0.5833        | 3.15  | 1300 | 0.5828          | 0.8439   |
| 0.8811        | 3.39  | 1400 | 0.6564          | 0.8259   |
| 0.5639        | 3.63  | 1500 | 0.5737          | 0.8439   |
| 0.639         | 3.87  | 1600 | 0.5609          | 0.8379   |
| 0.6455        | 4.12  | 1700 | 0.5820          | 0.8370   |
| 0.5402        | 4.36  | 1800 | 0.5797          | 0.8345   |
| 0.5311        | 4.6   | 1900 | 0.5511          | 0.8456   |
| 0.5734        | 4.84  | 2000 | 0.5444          | 0.8508   |
| 0.5206        | 5.08  | 2100 | 0.5326          | 0.8636   |
| 0.6272        | 5.33  | 2200 | 0.5478          | 0.8525   |
| 0.5124        | 5.57  | 2300 | 0.5296          | 0.8688   |
| 0.5659        | 5.81  | 2400 | 0.5181          | 0.8705   |
| 0.4212        | 6.05  | 2500 | 0.5200          | 0.8611   |
| 0.4338        | 6.3   | 2600 | 0.5135          | 0.8731   |
| 0.3407        | 6.54  | 2700 | 0.5147          | 0.8722   |
| 0.4043        | 6.78  | 2800 | 0.5081          | 0.8696   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

ace of clubs ace of diamonds five of hearts five of spades four of clubs four of diamonds four of hearts four of spades jack of clubs jack of diamonds jack of hearts jack of spades ace of hearts king of clubs king of diamonds king of hearts king of spades nine of clubs nine of diamonds nine of hearts nine of spades queen of clubs queen of diamonds ace of spades queen of hearts queen of spades seven of clubs seven of diamonds seven of hearts seven of spades six of clubs six of diamonds six of hearts six of spades eight of clubs ten of clubs ten of diamonds ten of hearts ten of spades three of clubs three of diamonds three of hearts three of spades two of clubs two of diamonds eight of diamonds two of hearts two of spades eight of hearts eight of spades five of clubs five of diamonds