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# hushem_40x_deit_base_rms_001_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: 4.0356
- Accuracy: 0.5581

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1943        | 1.0   | 217   | 1.3862          | 0.3488   |
| 1.2108        | 2.0   | 434   | 1.3456          | 0.3721   |
| 0.8764        | 3.0   | 651   | 1.3683          | 0.4884   |
| 0.7995        | 4.0   | 868   | 0.8441          | 0.5814   |
| 0.8665        | 5.0   | 1085  | 1.2083          | 0.5116   |
| 0.7433        | 6.0   | 1302  | 0.7858          | 0.7209   |
| 0.7205        | 7.0   | 1519  | 0.8439          | 0.6744   |
| 0.6415        | 8.0   | 1736  | 0.6198          | 0.6512   |
| 0.6773        | 9.0   | 1953  | 0.8169          | 0.6744   |
| 0.5449        | 10.0  | 2170  | 0.8224          | 0.6512   |
| 0.5225        | 11.0  | 2387  | 0.7556          | 0.7209   |
| 0.5268        | 12.0  | 2604  | 0.8703          | 0.6744   |
| 0.41          | 13.0  | 2821  | 0.7919          | 0.6512   |
| 0.4695        | 14.0  | 3038  | 0.9473          | 0.6744   |
| 0.3173        | 15.0  | 3255  | 1.2235          | 0.6512   |
| 0.3283        | 16.0  | 3472  | 1.3091          | 0.6512   |
| 0.3212        | 17.0  | 3689  | 1.0773          | 0.6047   |
| 0.3662        | 18.0  | 3906  | 0.9193          | 0.6279   |
| 0.3712        | 19.0  | 4123  | 0.9811          | 0.6744   |
| 0.3483        | 20.0  | 4340  | 1.5620          | 0.5814   |
| 0.2594        | 21.0  | 4557  | 1.8035          | 0.5814   |
| 0.3019        | 22.0  | 4774  | 1.3880          | 0.6744   |
| 0.2498        | 23.0  | 4991  | 1.6113          | 0.5814   |
| 0.2349        | 24.0  | 5208  | 1.2780          | 0.6047   |
| 0.1589        | 25.0  | 5425  | 1.6674          | 0.6512   |
| 0.2341        | 26.0  | 5642  | 1.6966          | 0.6512   |
| 0.1986        | 27.0  | 5859  | 1.4673          | 0.6047   |
| 0.1141        | 28.0  | 6076  | 1.6993          | 0.6512   |
| 0.1291        | 29.0  | 6293  | 2.0265          | 0.5581   |
| 0.1273        | 30.0  | 6510  | 1.8689          | 0.6279   |
| 0.0887        | 31.0  | 6727  | 1.4863          | 0.6977   |
| 0.101         | 32.0  | 6944  | 2.2258          | 0.6279   |
| 0.09          | 33.0  | 7161  | 1.6918          | 0.5814   |
| 0.063         | 34.0  | 7378  | 2.4040          | 0.5349   |
| 0.0263        | 35.0  | 7595  | 2.2869          | 0.5814   |
| 0.0357        | 36.0  | 7812  | 2.0118          | 0.6047   |
| 0.033         | 37.0  | 8029  | 2.5046          | 0.6279   |
| 0.0417        | 38.0  | 8246  | 2.0462          | 0.6512   |
| 0.0049        | 39.0  | 8463  | 3.1349          | 0.5814   |
| 0.0034        | 40.0  | 8680  | 2.4922          | 0.6279   |
| 0.0115        | 41.0  | 8897  | 2.7021          | 0.5581   |
| 0.0248        | 42.0  | 9114  | 3.1496          | 0.5116   |
| 0.0078        | 43.0  | 9331  | 2.6336          | 0.6279   |
| 0.0022        | 44.0  | 9548  | 3.2458          | 0.5349   |
| 0.0015        | 45.0  | 9765  | 3.3966          | 0.5349   |
| 0.0031        | 46.0  | 9982  | 4.1353          | 0.5116   |
| 0.0           | 47.0  | 10199 | 3.5481          | 0.5814   |
| 0.0002        | 48.0  | 10416 | 3.8712          | 0.5349   |
| 0.0           | 49.0  | 10633 | 4.0305          | 0.5581   |
| 0.0           | 50.0  | 10850 | 4.0356          | 0.5581   |


### 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