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# hushem_40x_deit_base_sgd_0001_fold3

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2710
- Accuracy: 0.4651

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3787        | 1.0   | 217   | 1.4567          | 0.2326   |
| 1.3411        | 2.0   | 434   | 1.4476          | 0.2326   |
| 1.3346        | 3.0   | 651   | 1.4398          | 0.2326   |
| 1.3522        | 4.0   | 868   | 1.4325          | 0.2558   |
| 1.295         | 5.0   | 1085  | 1.4257          | 0.2558   |
| 1.3027        | 6.0   | 1302  | 1.4192          | 0.2791   |
| 1.2908        | 7.0   | 1519  | 1.4129          | 0.3023   |
| 1.2684        | 8.0   | 1736  | 1.4068          | 0.3023   |
| 1.2597        | 9.0   | 1953  | 1.4007          | 0.3023   |
| 1.2504        | 10.0  | 2170  | 1.3948          | 0.3023   |
| 1.2181        | 11.0  | 2387  | 1.3891          | 0.3023   |
| 1.2286        | 12.0  | 2604  | 1.3834          | 0.3023   |
| 1.229         | 13.0  | 2821  | 1.3779          | 0.3023   |
| 1.2118        | 14.0  | 3038  | 1.3725          | 0.3256   |
| 1.1939        | 15.0  | 3255  | 1.3673          | 0.3256   |
| 1.2054        | 16.0  | 3472  | 1.3622          | 0.3488   |
| 1.1836        | 17.0  | 3689  | 1.3572          | 0.3721   |
| 1.1754        | 18.0  | 3906  | 1.3524          | 0.3721   |
| 1.1872        | 19.0  | 4123  | 1.3477          | 0.3721   |
| 1.1652        | 20.0  | 4340  | 1.3431          | 0.3721   |
| 1.1396        | 21.0  | 4557  | 1.3387          | 0.3721   |
| 1.1373        | 22.0  | 4774  | 1.3343          | 0.3953   |
| 1.1381        | 23.0  | 4991  | 1.3300          | 0.3953   |
| 1.101         | 24.0  | 5208  | 1.3259          | 0.3953   |
| 1.1305        | 25.0  | 5425  | 1.3219          | 0.4186   |
| 1.1458        | 26.0  | 5642  | 1.3181          | 0.4186   |
| 1.0969        | 27.0  | 5859  | 1.3143          | 0.4186   |
| 1.092         | 28.0  | 6076  | 1.3106          | 0.4186   |
| 1.0422        | 29.0  | 6293  | 1.3071          | 0.4186   |
| 1.07          | 30.0  | 6510  | 1.3037          | 0.4419   |
| 1.097         | 31.0  | 6727  | 1.3005          | 0.4419   |
| 1.1048        | 32.0  | 6944  | 1.2974          | 0.4419   |
| 1.0657        | 33.0  | 7161  | 1.2945          | 0.4419   |
| 1.0841        | 34.0  | 7378  | 1.2918          | 0.4419   |
| 1.0697        | 35.0  | 7595  | 1.2891          | 0.4419   |
| 1.0586        | 36.0  | 7812  | 1.2867          | 0.4419   |
| 1.0346        | 37.0  | 8029  | 1.2845          | 0.4419   |
| 1.0364        | 38.0  | 8246  | 1.2824          | 0.4651   |
| 1.055         | 39.0  | 8463  | 1.2804          | 0.4651   |
| 1.0391        | 40.0  | 8680  | 1.2787          | 0.4651   |
| 1.0408        | 41.0  | 8897  | 1.2771          | 0.4651   |
| 1.0911        | 42.0  | 9114  | 1.2757          | 0.4651   |
| 1.042         | 43.0  | 9331  | 1.2745          | 0.4651   |
| 1.0562        | 44.0  | 9548  | 1.2735          | 0.4651   |
| 1.0444        | 45.0  | 9765  | 1.2727          | 0.4651   |
| 1.0551        | 46.0  | 9982  | 1.2720          | 0.4651   |
| 1.0314        | 47.0  | 10199 | 1.2715          | 0.4651   |
| 1.067         | 48.0  | 10416 | 1.2712          | 0.4651   |
| 1.0573        | 49.0  | 10633 | 1.2710          | 0.4651   |
| 1.0022        | 50.0  | 10850 | 1.2710          | 0.4651   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

01_normal 02_tapered 03_pyriform 04_amorphous