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# hushem_40x_deit_base_sgd_0001_fold2

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: 1.2543
- Accuracy: 0.3333

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3992        | 1.0   | 215   | 1.3998          | 0.2667   |
| 1.3515        | 2.0   | 430   | 1.3921          | 0.3111   |
| 1.3529        | 3.0   | 645   | 1.3851          | 0.3111   |
| 1.3241        | 4.0   | 860   | 1.3787          | 0.3111   |
| 1.3174        | 5.0   | 1075  | 1.3730          | 0.3333   |
| 1.331         | 6.0   | 1290  | 1.3675          | 0.3333   |
| 1.3242        | 7.0   | 1505  | 1.3623          | 0.3333   |
| 1.2565        | 8.0   | 1720  | 1.3574          | 0.3111   |
| 1.2719        | 9.0   | 1935  | 1.3525          | 0.3333   |
| 1.2647        | 10.0  | 2150  | 1.3477          | 0.3333   |
| 1.2293        | 11.0  | 2365  | 1.3430          | 0.3556   |
| 1.1981        | 12.0  | 2580  | 1.3386          | 0.3556   |
| 1.2258        | 13.0  | 2795  | 1.3342          | 0.3556   |
| 1.1901        | 14.0  | 3010  | 1.3299          | 0.3111   |
| 1.1988        | 15.0  | 3225  | 1.3257          | 0.3333   |
| 1.2048        | 16.0  | 3440  | 1.3214          | 0.3333   |
| 1.1848        | 17.0  | 3655  | 1.3173          | 0.3333   |
| 1.1799        | 18.0  | 3870  | 1.3134          | 0.3333   |
| 1.1629        | 19.0  | 4085  | 1.3095          | 0.3333   |
| 1.1482        | 20.0  | 4300  | 1.3058          | 0.3333   |
| 1.1478        | 21.0  | 4515  | 1.3022          | 0.3333   |
| 1.1472        | 22.0  | 4730  | 1.2988          | 0.3333   |
| 1.1143        | 23.0  | 4945  | 1.2955          | 0.3333   |
| 1.1122        | 24.0  | 5160  | 1.2923          | 0.3333   |
| 1.1           | 25.0  | 5375  | 1.2893          | 0.3111   |
| 1.1089        | 26.0  | 5590  | 1.2864          | 0.3111   |
| 1.1001        | 27.0  | 5805  | 1.2836          | 0.3333   |
| 1.0858        | 28.0  | 6020  | 1.2810          | 0.3333   |
| 1.093         | 29.0  | 6235  | 1.2786          | 0.3333   |
| 1.081         | 30.0  | 6450  | 1.2761          | 0.3333   |
| 1.0426        | 31.0  | 6665  | 1.2739          | 0.3333   |
| 1.0757        | 32.0  | 6880  | 1.2718          | 0.3333   |
| 1.0524        | 33.0  | 7095  | 1.2698          | 0.3333   |
| 1.0725        | 34.0  | 7310  | 1.2680          | 0.3333   |
| 1.055         | 35.0  | 7525  | 1.2662          | 0.3333   |
| 1.0308        | 36.0  | 7740  | 1.2646          | 0.3333   |
| 1.0978        | 37.0  | 7955  | 1.2631          | 0.3333   |
| 1.0264        | 38.0  | 8170  | 1.2617          | 0.3333   |
| 1.0508        | 39.0  | 8385  | 1.2604          | 0.3333   |
| 1.0208        | 40.0  | 8600  | 1.2593          | 0.3333   |
| 1.0505        | 41.0  | 8815  | 1.2583          | 0.3333   |
| 1.0147        | 42.0  | 9030  | 1.2574          | 0.3333   |
| 1.0355        | 43.0  | 9245  | 1.2566          | 0.3333   |
| 1.0064        | 44.0  | 9460  | 1.2559          | 0.3333   |
| 1.019         | 45.0  | 9675  | 1.2554          | 0.3333   |
| 1.0292        | 46.0  | 9890  | 1.2549          | 0.3333   |
| 1.0584        | 47.0  | 10105 | 1.2546          | 0.3333   |
| 1.0425        | 48.0  | 10320 | 1.2544          | 0.3333   |
| 1.0211        | 49.0  | 10535 | 1.2543          | 0.3333   |
| 1.0221        | 50.0  | 10750 | 1.2543          | 0.3333   |


### 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