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# vit-base-patch16-224-rotated-dungeons-v101

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the rotated_maps dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6993
- Accuracy: 0.8333

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.799         | 0.8333  | 10   | 1.9456          | 0.1667   |
| 1.2417        | 1.6667  | 20   | 1.7680          | 0.3333   |
| 1.1543        | 2.5     | 30   | 1.5470          | 0.5      |
| 0.8829        | 3.3333  | 40   | 1.4117          | 0.5      |
| 0.8725        | 4.1667  | 50   | 1.2967          | 0.5      |
| 0.5514        | 5.0     | 60   | 1.1901          | 0.5      |
| 0.4565        | 5.8333  | 70   | 1.1867          | 0.5      |
| 0.3663        | 6.6667  | 80   | 1.0417          | 0.5      |
| 0.3448        | 7.5     | 90   | 0.8938          | 0.6667   |
| 0.2525        | 8.3333  | 100  | 0.8804          | 0.75     |
| 0.1729        | 9.1667  | 110  | 0.9067          | 0.6667   |
| 0.1848        | 10.0    | 120  | 0.8441          | 0.6667   |
| 0.1847        | 10.8333 | 130  | 0.7352          | 0.8333   |
| 0.0916        | 11.6667 | 140  | 0.7336          | 0.8333   |
| 0.1771        | 12.5    | 150  | 0.7012          | 0.8333   |
| 0.105         | 13.3333 | 160  | 0.7030          | 0.8333   |
| 0.1008        | 14.1667 | 170  | 0.7004          | 0.8333   |
| 0.1127        | 15.0    | 180  | 0.6993          | 0.8333   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1

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