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# hushem_40x_deit_small_sgd_001_fold2

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9318
- Accuracy: 0.7333

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1891        | 1.0   | 215   | 1.3300          | 0.3778   |
| 0.9647        | 2.0   | 430   | 1.2794          | 0.4444   |
| 0.8581        | 3.0   | 645   | 1.2244          | 0.5111   |
| 0.699         | 4.0   | 860   | 1.1784          | 0.5333   |
| 0.6158        | 5.0   | 1075  | 1.1498          | 0.5111   |
| 0.5391        | 6.0   | 1290  | 1.1059          | 0.5556   |
| 0.4953        | 7.0   | 1505  | 1.0650          | 0.5333   |
| 0.4016        | 8.0   | 1720  | 1.0249          | 0.5556   |
| 0.3397        | 9.0   | 1935  | 0.9796          | 0.6222   |
| 0.3003        | 10.0  | 2150  | 0.9463          | 0.7111   |
| 0.246         | 11.0  | 2365  | 0.9270          | 0.7111   |
| 0.1949        | 12.0  | 2580  | 0.9025          | 0.7111   |
| 0.1895        | 13.0  | 2795  | 0.8872          | 0.7111   |
| 0.1659        | 14.0  | 3010  | 0.8723          | 0.7111   |
| 0.1576        | 15.0  | 3225  | 0.8544          | 0.7111   |
| 0.1305        | 16.0  | 3440  | 0.8521          | 0.7111   |
| 0.1123        | 17.0  | 3655  | 0.8414          | 0.7111   |
| 0.1025        | 18.0  | 3870  | 0.8453          | 0.7111   |
| 0.0749        | 19.0  | 4085  | 0.8597          | 0.7111   |
| 0.0854        | 20.0  | 4300  | 0.8467          | 0.7111   |
| 0.0788        | 21.0  | 4515  | 0.8314          | 0.7111   |
| 0.0675        | 22.0  | 4730  | 0.8392          | 0.7111   |
| 0.0523        | 23.0  | 4945  | 0.8293          | 0.7111   |
| 0.0556        | 24.0  | 5160  | 0.8555          | 0.7111   |
| 0.0483        | 25.0  | 5375  | 0.8566          | 0.7111   |
| 0.0417        | 26.0  | 5590  | 0.8533          | 0.7111   |
| 0.0397        | 27.0  | 5805  | 0.8560          | 0.7333   |
| 0.0302        | 28.0  | 6020  | 0.8587          | 0.7333   |
| 0.0286        | 29.0  | 6235  | 0.8633          | 0.7333   |
| 0.0386        | 30.0  | 6450  | 0.8691          | 0.7333   |
| 0.0212        | 31.0  | 6665  | 0.8693          | 0.7333   |
| 0.0221        | 32.0  | 6880  | 0.8714          | 0.7333   |
| 0.0198        | 33.0  | 7095  | 0.8818          | 0.7333   |
| 0.0189        | 34.0  | 7310  | 0.8880          | 0.7333   |
| 0.0167        | 35.0  | 7525  | 0.8939          | 0.7333   |
| 0.0198        | 36.0  | 7740  | 0.9010          | 0.7333   |
| 0.0157        | 37.0  | 7955  | 0.8988          | 0.7333   |
| 0.0177        | 38.0  | 8170  | 0.9154          | 0.7333   |
| 0.0136        | 39.0  | 8385  | 0.9094          | 0.7333   |
| 0.0108        | 40.0  | 8600  | 0.9213          | 0.7333   |
| 0.0119        | 41.0  | 8815  | 0.9173          | 0.7333   |
| 0.0127        | 42.0  | 9030  | 0.9219          | 0.7333   |
| 0.0095        | 43.0  | 9245  | 0.9256          | 0.7333   |
| 0.0124        | 44.0  | 9460  | 0.9223          | 0.7333   |
| 0.0112        | 45.0  | 9675  | 0.9246          | 0.7333   |
| 0.0112        | 46.0  | 9890  | 0.9266          | 0.7333   |
| 0.0102        | 47.0  | 10105 | 0.9301          | 0.7333   |
| 0.0105        | 48.0  | 10320 | 0.9338          | 0.7333   |
| 0.0119        | 49.0  | 10535 | 0.9314          | 0.7333   |
| 0.0144        | 50.0  | 10750 | 0.9318          | 0.7333   |


### 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