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# vit-large-patch16-224-dungeons-001

This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6325
- Accuracy: 0.75

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 85
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.8218        | 6.6667  | 10   | 1.8564          | 0.1667   |
| 1.4325        | 13.3333 | 20   | 1.7325          | 0.3333   |
| 0.8869        | 20.0    | 30   | 1.5186          | 0.4167   |
| 0.3717        | 26.6667 | 40   | 1.1131          | 0.6667   |
| 0.0945        | 33.3333 | 50   | 0.8408          | 0.75     |
| 0.0175        | 40.0    | 60   | 0.7224          | 0.75     |
| 0.0051        | 46.6667 | 70   | 0.6674          | 0.75     |
| 0.0024        | 53.3333 | 80   | 0.6325          | 0.75     |


### Framework versions

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

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