
<!-- 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-fold1

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: 0.9744
- 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    | 1.2772          | 0.0909   |
| No log        | 2.0   | 2    | 1.1448          | 0.1818   |
| No log        | 3.0   | 3    | 0.9744          | 0.7273   |
| No log        | 4.0   | 4    | 0.9234          | 0.7273   |
| No log        | 5.0   | 5    | 1.0760          | 0.7273   |
| No log        | 6.0   | 6    | 1.3222          | 0.7273   |
| No log        | 7.0   | 7    | 1.5248          | 0.7273   |
| No log        | 8.0   | 8    | 1.6139          | 0.7273   |
| No log        | 9.0   | 9    | 1.6711          | 0.7273   |
| 0.3554        | 10.0  | 10   | 1.7354          | 0.7273   |
| 0.3554        | 11.0  | 11   | 1.6721          | 0.7273   |
| 0.3554        | 12.0  | 12   | 1.5988          | 0.7273   |
| 0.3554        | 13.0  | 13   | 1.5960          | 0.7273   |
| 0.3554        | 14.0  | 14   | 1.5832          | 0.7273   |
| 0.3554        | 15.0  | 15   | 1.5683          | 0.7273   |
| 0.3554        | 16.0  | 16   | 1.5774          | 0.7273   |
| 0.3554        | 17.0  | 17   | 1.6468          | 0.7273   |
| 0.3554        | 18.0  | 18   | 1.7091          | 0.7273   |
| 0.3554        | 19.0  | 19   | 1.7276          | 0.7273   |
| 0.1335        | 20.0  | 20   | 1.7052          | 0.7273   |
| 0.1335        | 21.0  | 21   | 1.6426          | 0.7273   |
| 0.1335        | 22.0  | 22   | 1.5316          | 0.7273   |
| 0.1335        | 23.0  | 23   | 1.4017          | 0.7273   |
| 0.1335        | 24.0  | 24   | 1.3009          | 0.7273   |
| 0.1335        | 25.0  | 25   | 1.2864          | 0.7273   |
| 0.1335        | 26.0  | 26   | 1.3934          | 0.7273   |
| 0.1335        | 27.0  | 27   | 1.4436          | 0.7273   |
| 0.1335        | 28.0  | 28   | 1.5752          | 0.7273   |
| 0.1335        | 29.0  | 29   | 1.6211          | 0.7273   |
| 0.0769        | 30.0  | 30   | 1.5944          | 0.7273   |
| 0.0769        | 31.0  | 31   | 1.5283          | 0.7273   |
| 0.0769        | 32.0  | 32   | 1.4341          | 0.7273   |
| 0.0769        | 33.0  | 33   | 1.4512          | 0.7273   |
| 0.0769        | 34.0  | 34   | 1.4980          | 0.7273   |
| 0.0769        | 35.0  | 35   | 1.5803          | 0.7273   |
| 0.0769        | 36.0  | 36   | 1.7676          | 0.7273   |
| 0.0769        | 37.0  | 37   | 1.8581          | 0.7273   |
| 0.0769        | 38.0  | 38   | 1.8816          | 0.7273   |
| 0.0769        | 39.0  | 39   | 1.8317          | 0.7273   |
| 0.0505        | 40.0  | 40   | 1.7445          | 0.7273   |
| 0.0505        | 41.0  | 41   | 1.6965          | 0.7273   |
| 0.0505        | 42.0  | 42   | 1.7210          | 0.7273   |
| 0.0505        | 43.0  | 43   | 1.6903          | 0.7273   |
| 0.0505        | 44.0  | 44   | 1.6944          | 0.7273   |
| 0.0505        | 45.0  | 45   | 1.6923          | 0.7273   |
| 0.0505        | 46.0  | 46   | 1.7470          | 0.7273   |
| 0.0505        | 47.0  | 47   | 1.7502          | 0.7273   |
| 0.0505        | 48.0  | 48   | 1.7739          | 0.7273   |
| 0.0505        | 49.0  | 49   | 1.7819          | 0.7273   |
| 0.0255        | 50.0  | 50   | 1.8200          | 0.7273   |
| 0.0255        | 51.0  | 51   | 1.8122          | 0.7273   |
| 0.0255        | 52.0  | 52   | 1.7939          | 0.7273   |
| 0.0255        | 53.0  | 53   | 1.7736          | 0.7273   |
| 0.0255        | 54.0  | 54   | 1.7411          | 0.7273   |
| 0.0255        | 55.0  | 55   | 1.6773          | 0.7273   |
| 0.0255        | 56.0  | 56   | 1.6556          | 0.7273   |
| 0.0255        | 57.0  | 57   | 1.6767          | 0.7273   |
| 0.0255        | 58.0  | 58   | 1.6623          | 0.7273   |
| 0.0255        | 59.0  | 59   | 1.6553          | 0.7273   |
| 0.0227        | 60.0  | 60   | 1.6682          | 0.7273   |
| 0.0227        | 61.0  | 61   | 1.6209          | 0.7273   |
| 0.0227        | 62.0  | 62   | 1.6188          | 0.7273   |
| 0.0227        | 63.0  | 63   | 1.6919          | 0.7273   |
| 0.0227        | 64.0  | 64   | 1.7957          | 0.7273   |
| 0.0227        | 65.0  | 65   | 1.8750          | 0.7273   |
| 0.0227        | 66.0  | 66   | 1.9156          | 0.7273   |
| 0.0227        | 67.0  | 67   | 1.9163          | 0.7273   |
| 0.0227        | 68.0  | 68   | 1.8969          | 0.7273   |
| 0.0227        | 69.0  | 69   | 1.8814          | 0.7273   |
| 0.0185        | 70.0  | 70   | 1.8715          | 0.7273   |
| 0.0185        | 71.0  | 71   | 1.8892          | 0.7273   |
| 0.0185        | 72.0  | 72   | 1.9383          | 0.7273   |
| 0.0185        | 73.0  | 73   | 1.9627          | 0.7273   |
| 0.0185        | 74.0  | 74   | 2.0154          | 0.7273   |
| 0.0185        | 75.0  | 75   | 2.0326          | 0.7273   |
| 0.0185        | 76.0  | 76   | 2.0425          | 0.7273   |
| 0.0185        | 77.0  | 77   | 2.0586          | 0.7273   |
| 0.0185        | 78.0  | 78   | 2.0582          | 0.7273   |
| 0.0185        | 79.0  | 79   | 2.0863          | 0.7273   |
| 0.0246        | 80.0  | 80   | 2.1233          | 0.7273   |
| 0.0246        | 81.0  | 81   | 2.1527          | 0.7273   |
| 0.0246        | 82.0  | 82   | 2.1760          | 0.7273   |
| 0.0246        | 83.0  | 83   | 2.1907          | 0.7273   |
| 0.0246        | 84.0  | 84   | 2.1859          | 0.7273   |
| 0.0246        | 85.0  | 85   | 2.1654          | 0.7273   |
| 0.0246        | 86.0  | 86   | 2.1479          | 0.7273   |
| 0.0246        | 87.0  | 87   | 2.1194          | 0.7273   |
| 0.0246        | 88.0  | 88   | 2.1059          | 0.7273   |
| 0.0246        | 89.0  | 89   | 2.1032          | 0.7273   |
| 0.0228        | 90.0  | 90   | 2.0999          | 0.7273   |
| 0.0228        | 91.0  | 91   | 2.1037          | 0.7273   |
| 0.0228        | 92.0  | 92   | 2.1026          | 0.7273   |
| 0.0228        | 93.0  | 93   | 2.1132          | 0.7273   |
| 0.0228        | 94.0  | 94   | 2.1302          | 0.7273   |
| 0.0228        | 95.0  | 95   | 2.1453          | 0.7273   |
| 0.0228        | 96.0  | 96   | 2.1634          | 0.7273   |
| 0.0228        | 97.0  | 97   | 2.1762          | 0.7273   |
| 0.0228        | 98.0  | 98   | 2.1859          | 0.7273   |
| 0.0228        | 99.0  | 99   | 2.1916          | 0.7273   |
| 0.0142        | 100.0 | 100  | 2.1933          | 0.7273   |


### Framework versions

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

hafi̇f orta şi̇ddetli̇