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# hushem_40x_deit_base_sgd_0001_fold4

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: 1.2151
- Accuracy: 0.4286

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3918        | 1.0   | 219   | 1.4045          | 0.3095   |
| 1.3704        | 2.0   | 438   | 1.3956          | 0.3095   |
| 1.3491        | 3.0   | 657   | 1.3880          | 0.3333   |
| 1.3369        | 4.0   | 876   | 1.3811          | 0.3333   |
| 1.3406        | 5.0   | 1095  | 1.3747          | 0.3333   |
| 1.3171        | 6.0   | 1314  | 1.3686          | 0.3333   |
| 1.2982        | 7.0   | 1533  | 1.3628          | 0.3571   |
| 1.2896        | 8.0   | 1752  | 1.3571          | 0.3571   |
| 1.2549        | 9.0   | 1971  | 1.3513          | 0.3810   |
| 1.2384        | 10.0  | 2190  | 1.3457          | 0.4048   |
| 1.2507        | 11.0  | 2409  | 1.3401          | 0.4286   |
| 1.2362        | 12.0  | 2628  | 1.3346          | 0.4286   |
| 1.1966        | 13.0  | 2847  | 1.3293          | 0.4286   |
| 1.2279        | 14.0  | 3066  | 1.3240          | 0.4286   |
| 1.2136        | 15.0  | 3285  | 1.3188          | 0.4286   |
| 1.1856        | 16.0  | 3504  | 1.3138          | 0.4286   |
| 1.1941        | 17.0  | 3723  | 1.3088          | 0.4286   |
| 1.1805        | 18.0  | 3942  | 1.3039          | 0.4286   |
| 1.1554        | 19.0  | 4161  | 1.2991          | 0.4048   |
| 1.1709        | 20.0  | 4380  | 1.2943          | 0.4048   |
| 1.1523        | 21.0  | 4599  | 1.2895          | 0.4048   |
| 1.138         | 22.0  | 4818  | 1.2848          | 0.4048   |
| 1.0984        | 23.0  | 5037  | 1.2803          | 0.4048   |
| 1.1405        | 24.0  | 5256  | 1.2759          | 0.4048   |
| 1.1028        | 25.0  | 5475  | 1.2716          | 0.4286   |
| 1.1236        | 26.0  | 5694  | 1.2674          | 0.4286   |
| 1.0819        | 27.0  | 5913  | 1.2634          | 0.4286   |
| 1.1245        | 28.0  | 6132  | 1.2595          | 0.4286   |
| 1.0929        | 29.0  | 6351  | 1.2557          | 0.4286   |
| 1.0861        | 30.0  | 6570  | 1.2521          | 0.4048   |
| 1.082         | 31.0  | 6789  | 1.2486          | 0.4048   |
| 1.0826        | 32.0  | 7008  | 1.2452          | 0.4048   |
| 1.0889        | 33.0  | 7227  | 1.2420          | 0.4048   |
| 1.052         | 34.0  | 7446  | 1.2390          | 0.4286   |
| 1.056         | 35.0  | 7665  | 1.2361          | 0.4286   |
| 1.0391        | 36.0  | 7884  | 1.2333          | 0.4286   |
| 1.0236        | 37.0  | 8103  | 1.2307          | 0.4286   |
| 1.0474        | 38.0  | 8322  | 1.2283          | 0.4286   |
| 1.0069        | 39.0  | 8541  | 1.2261          | 0.4286   |
| 1.0443        | 40.0  | 8760  | 1.2242          | 0.4286   |
| 1.0711        | 41.0  | 8979  | 1.2223          | 0.4048   |
| 1.053         | 42.0  | 9198  | 1.2207          | 0.4286   |
| 1.0356        | 43.0  | 9417  | 1.2193          | 0.4286   |
| 1.0491        | 44.0  | 9636  | 1.2181          | 0.4286   |
| 0.9928        | 45.0  | 9855  | 1.2171          | 0.4286   |
| 1.0402        | 46.0  | 10074 | 1.2163          | 0.4286   |
| 1.0792        | 47.0  | 10293 | 1.2157          | 0.4286   |
| 1.0146        | 48.0  | 10512 | 1.2153          | 0.4286   |
| 1.0325        | 49.0  | 10731 | 1.2152          | 0.4286   |
| 1.0249        | 50.0  | 10950 | 1.2151          | 0.4286   |


### 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