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# hushem_40x_deit_base_rms_001_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: 1.7808
- Accuracy: 0.8095

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4095        | 1.0   | 219   | 1.4091          | 0.2381   |
| 1.3846        | 2.0   | 438   | 1.3865          | 0.2381   |
| 1.2802        | 3.0   | 657   | 1.3372          | 0.2381   |
| 1.1537        | 4.0   | 876   | 1.4032          | 0.2619   |
| 1.177         | 5.0   | 1095  | 1.3147          | 0.4286   |
| 1.1719        | 6.0   | 1314  | 0.9703          | 0.6667   |
| 1.0403        | 7.0   | 1533  | 1.2271          | 0.4762   |
| 0.9188        | 8.0   | 1752  | 0.9431          | 0.5714   |
| 0.8565        | 9.0   | 1971  | 1.0056          | 0.5952   |
| 0.8519        | 10.0  | 2190  | 0.7845          | 0.6429   |
| 0.7519        | 11.0  | 2409  | 0.7049          | 0.6905   |
| 0.8514        | 12.0  | 2628  | 0.6628          | 0.7857   |
| 0.8808        | 13.0  | 2847  | 0.8006          | 0.7381   |
| 0.796         | 14.0  | 3066  | 0.7332          | 0.6905   |
| 0.7213        | 15.0  | 3285  | 0.7486          | 0.6905   |
| 0.663         | 16.0  | 3504  | 0.4390          | 0.7857   |
| 0.5845        | 17.0  | 3723  | 0.9856          | 0.5952   |
| 0.5228        | 18.0  | 3942  | 0.6588          | 0.7381   |
| 0.5581        | 19.0  | 4161  | 0.6093          | 0.8571   |
| 0.518         | 20.0  | 4380  | 0.5316          | 0.6905   |
| 0.5058        | 21.0  | 4599  | 0.7052          | 0.7381   |
| 0.453         | 22.0  | 4818  | 0.6155          | 0.7143   |
| 0.4128        | 23.0  | 5037  | 0.7141          | 0.7381   |
| 0.44          | 24.0  | 5256  | 0.6896          | 0.7619   |
| 0.3933        | 25.0  | 5475  | 0.6353          | 0.7619   |
| 0.3648        | 26.0  | 5694  | 0.7225          | 0.8095   |
| 0.2677        | 27.0  | 5913  | 0.6987          | 0.8810   |
| 0.3023        | 28.0  | 6132  | 0.8143          | 0.8333   |
| 0.332         | 29.0  | 6351  | 0.8300          | 0.8333   |
| 0.2772        | 30.0  | 6570  | 0.6339          | 0.7619   |
| 0.1878        | 31.0  | 6789  | 0.6694          | 0.8333   |
| 0.2152        | 32.0  | 7008  | 0.7930          | 0.7619   |
| 0.2378        | 33.0  | 7227  | 0.7856          | 0.7619   |
| 0.1874        | 34.0  | 7446  | 0.6614          | 0.8571   |
| 0.2043        | 35.0  | 7665  | 0.7218          | 0.8095   |
| 0.122         | 36.0  | 7884  | 1.0415          | 0.8333   |
| 0.1837        | 37.0  | 8103  | 1.2016          | 0.7381   |
| 0.1148        | 38.0  | 8322  | 0.8289          | 0.7857   |
| 0.0825        | 39.0  | 8541  | 1.4711          | 0.7381   |
| 0.0828        | 40.0  | 8760  | 0.9405          | 0.8810   |
| 0.0736        | 41.0  | 8979  | 1.4104          | 0.8810   |
| 0.0864        | 42.0  | 9198  | 1.1297          | 0.8333   |
| 0.0176        | 43.0  | 9417  | 1.2293          | 0.7857   |
| 0.0392        | 44.0  | 9636  | 1.3878          | 0.8095   |
| 0.0272        | 45.0  | 9855  | 1.2021          | 0.8571   |
| 0.0125        | 46.0  | 10074 | 2.3102          | 0.7619   |
| 0.0149        | 47.0  | 10293 | 1.8621          | 0.7857   |
| 0.0032        | 48.0  | 10512 | 1.7899          | 0.8333   |
| 0.0016        | 49.0  | 10731 | 1.9528          | 0.8095   |
| 0.0001        | 50.0  | 10950 | 1.7808          | 0.8095   |


### 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