
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# deit-base-distilled-patch16-224-hasta-85-fold2

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0159
- Accuracy: 0.7273

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 1.3509          | 0.1818   |
| No log        | 2.0   | 2    | 1.2094          | 0.1818   |
| No log        | 3.0   | 3    | 1.0159          | 0.7273   |
| No log        | 4.0   | 4    | 0.9047          | 0.6364   |
| No log        | 5.0   | 5    | 0.9481          | 0.7273   |
| No log        | 6.0   | 6    | 1.1337          | 0.7273   |
| No log        | 7.0   | 7    | 1.2464          | 0.7273   |
| No log        | 8.0   | 8    | 1.2335          | 0.7273   |
| No log        | 9.0   | 9    | 1.1432          | 0.7273   |
| 0.4248        | 10.0  | 10   | 1.0979          | 0.7273   |
| 0.4248        | 11.0  | 11   | 1.1069          | 0.7273   |
| 0.4248        | 12.0  | 12   | 1.1633          | 0.7273   |
| 0.4248        | 13.0  | 13   | 1.1650          | 0.7273   |
| 0.4248        | 14.0  | 14   | 1.1332          | 0.7273   |
| 0.4248        | 15.0  | 15   | 1.1423          | 0.7273   |
| 0.4248        | 16.0  | 16   | 1.1208          | 0.7273   |
| 0.4248        | 17.0  | 17   | 1.0566          | 0.7273   |
| 0.4248        | 18.0  | 18   | 1.0348          | 0.7273   |
| 0.4248        | 19.0  | 19   | 1.0146          | 0.7273   |
| 0.1813        | 20.0  | 20   | 1.0062          | 0.7273   |
| 0.1813        | 21.0  | 21   | 1.0748          | 0.7273   |
| 0.1813        | 22.0  | 22   | 1.1673          | 0.7273   |
| 0.1813        | 23.0  | 23   | 1.2477          | 0.7273   |
| 0.1813        | 24.0  | 24   | 1.2457          | 0.7273   |
| 0.1813        | 25.0  | 25   | 1.1424          | 0.7273   |
| 0.1813        | 26.0  | 26   | 1.0439          | 0.7273   |
| 0.1813        | 27.0  | 27   | 0.9436          | 0.7273   |
| 0.1813        | 28.0  | 28   | 0.8254          | 0.7273   |
| 0.1813        | 29.0  | 29   | 0.7963          | 0.7273   |
| 0.1021        | 30.0  | 30   | 0.8055          | 0.7273   |
| 0.1021        | 31.0  | 31   | 0.7734          | 0.7273   |
| 0.1021        | 32.0  | 32   | 0.7069          | 0.7273   |
| 0.1021        | 33.0  | 33   | 0.7235          | 0.7273   |
| 0.1021        | 34.0  | 34   | 0.8200          | 0.7273   |
| 0.1021        | 35.0  | 35   | 0.8484          | 0.7273   |
| 0.1021        | 36.0  | 36   | 0.9380          | 0.7273   |
| 0.1021        | 37.0  | 37   | 1.0584          | 0.7273   |
| 0.1021        | 38.0  | 38   | 1.1803          | 0.7273   |
| 0.1021        | 39.0  | 39   | 1.2916          | 0.7273   |
| 0.0579        | 40.0  | 40   | 1.3442          | 0.7273   |
| 0.0579        | 41.0  | 41   | 1.3060          | 0.7273   |
| 0.0579        | 42.0  | 42   | 1.2349          | 0.7273   |
| 0.0579        | 43.0  | 43   | 1.1867          | 0.7273   |
| 0.0579        | 44.0  | 44   | 1.1411          | 0.7273   |
| 0.0579        | 45.0  | 45   | 1.2009          | 0.7273   |
| 0.0579        | 46.0  | 46   | 1.2366          | 0.7273   |
| 0.0579        | 47.0  | 47   | 1.2790          | 0.7273   |
| 0.0579        | 48.0  | 48   | 1.3573          | 0.7273   |
| 0.0579        | 49.0  | 49   | 1.4175          | 0.7273   |
| 0.0436        | 50.0  | 50   | 1.4130          | 0.7273   |
| 0.0436        | 51.0  | 51   | 1.4465          | 0.7273   |
| 0.0436        | 52.0  | 52   | 1.4372          | 0.7273   |
| 0.0436        | 53.0  | 53   | 1.4207          | 0.7273   |
| 0.0436        | 54.0  | 54   | 1.4134          | 0.7273   |
| 0.0436        | 55.0  | 55   | 1.4889          | 0.7273   |
| 0.0436        | 56.0  | 56   | 1.5351          | 0.7273   |
| 0.0436        | 57.0  | 57   | 1.5673          | 0.7273   |
| 0.0436        | 58.0  | 58   | 1.5803          | 0.7273   |
| 0.0436        | 59.0  | 59   | 1.5685          | 0.7273   |
| 0.0325        | 60.0  | 60   | 1.5487          | 0.7273   |
| 0.0325        | 61.0  | 61   | 1.4888          | 0.7273   |
| 0.0325        | 62.0  | 62   | 1.4026          | 0.7273   |
| 0.0325        | 63.0  | 63   | 1.2968          | 0.7273   |
| 0.0325        | 64.0  | 64   | 1.2915          | 0.7273   |
| 0.0325        | 65.0  | 65   | 1.3016          | 0.7273   |
| 0.0325        | 66.0  | 66   | 1.3871          | 0.7273   |
| 0.0325        | 67.0  | 67   | 1.5019          | 0.7273   |
| 0.0325        | 68.0  | 68   | 1.6563          | 0.7273   |
| 0.0325        | 69.0  | 69   | 1.8046          | 0.7273   |
| 0.028         | 70.0  | 70   | 1.9155          | 0.7273   |
| 0.028         | 71.0  | 71   | 1.9688          | 0.7273   |
| 0.028         | 72.0  | 72   | 1.9570          | 0.7273   |
| 0.028         | 73.0  | 73   | 1.8879          | 0.7273   |
| 0.028         | 74.0  | 74   | 1.8354          | 0.7273   |
| 0.028         | 75.0  | 75   | 1.7812          | 0.7273   |
| 0.028         | 76.0  | 76   | 1.6800          | 0.7273   |
| 0.028         | 77.0  | 77   | 1.5444          | 0.7273   |
| 0.028         | 78.0  | 78   | 1.4488          | 0.7273   |
| 0.028         | 79.0  | 79   | 1.3880          | 0.7273   |
| 0.0411        | 80.0  | 80   | 1.3544          | 0.7273   |
| 0.0411        | 81.0  | 81   | 1.3867          | 0.7273   |
| 0.0411        | 82.0  | 82   | 1.4348          | 0.7273   |
| 0.0411        | 83.0  | 83   | 1.4906          | 0.7273   |
| 0.0411        | 84.0  | 84   | 1.5685          | 0.7273   |
| 0.0411        | 85.0  | 85   | 1.6276          | 0.7273   |
| 0.0411        | 86.0  | 86   | 1.6793          | 0.7273   |
| 0.0411        | 87.0  | 87   | 1.7099          | 0.7273   |
| 0.0411        | 88.0  | 88   | 1.7182          | 0.7273   |
| 0.0411        | 89.0  | 89   | 1.7049          | 0.7273   |
| 0.0343        | 90.0  | 90   | 1.6831          | 0.7273   |
| 0.0343        | 91.0  | 91   | 1.6695          | 0.7273   |
| 0.0343        | 92.0  | 92   | 1.6584          | 0.7273   |
| 0.0343        | 93.0  | 93   | 1.6467          | 0.7273   |
| 0.0343        | 94.0  | 94   | 1.6294          | 0.7273   |
| 0.0343        | 95.0  | 95   | 1.6147          | 0.7273   |
| 0.0343        | 96.0  | 96   | 1.6055          | 0.7273   |
| 0.0343        | 97.0  | 97   | 1.6026          | 0.7273   |
| 0.0343        | 98.0  | 98   | 1.6043          | 0.7273   |
| 0.0343        | 99.0  | 99   | 1.6039          | 0.7273   |
| 0.021         | 100.0 | 100  | 1.6044          | 0.7273   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

hafi̇f orta şi̇ddetli̇