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# hushem_40x_deit_base_rms_0001_fold5

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: 1.7342
- Accuracy: 0.8537

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0617        | 1.0   | 220   | 0.4998          | 0.8780   |
| 0.0015        | 2.0   | 440   | 0.4091          | 0.9024   |
| 0.067         | 3.0   | 660   | 0.7752          | 0.9024   |
| 0.0007        | 4.0   | 880   | 0.7710          | 0.8293   |
| 0.0006        | 5.0   | 1100  | 0.9905          | 0.8293   |
| 0.0109        | 6.0   | 1320  | 1.1163          | 0.8049   |
| 0.0           | 7.0   | 1540  | 1.0399          | 0.8049   |
| 0.0           | 8.0   | 1760  | 1.0747          | 0.8293   |
| 0.0           | 9.0   | 1980  | 1.1399          | 0.8537   |
| 0.0           | 10.0  | 2200  | 1.2260          | 0.8537   |
| 0.0           | 11.0  | 2420  | 1.3150          | 0.8537   |
| 0.0           | 12.0  | 2640  | 1.3880          | 0.8537   |
| 0.0           | 13.0  | 2860  | 1.4421          | 0.8537   |
| 0.0           | 14.0  | 3080  | 1.4689          | 0.8537   |
| 0.0           | 15.0  | 3300  | 1.4886          | 0.8537   |
| 0.0           | 16.0  | 3520  | 1.5214          | 0.8537   |
| 0.0           | 17.0  | 3740  | 1.5517          | 0.8537   |
| 0.0           | 18.0  | 3960  | 1.5796          | 0.8537   |
| 0.0           | 19.0  | 4180  | 1.6055          | 0.8537   |
| 0.0           | 20.0  | 4400  | 1.6255          | 0.8537   |
| 0.0           | 21.0  | 4620  | 1.6409          | 0.8537   |
| 0.0           | 22.0  | 4840  | 1.6535          | 0.8537   |
| 0.0           | 23.0  | 5060  | 1.6637          | 0.8537   |
| 0.0           | 24.0  | 5280  | 1.6723          | 0.8537   |
| 0.0           | 25.0  | 5500  | 1.6796          | 0.8537   |
| 0.0           | 26.0  | 5720  | 1.6858          | 0.8537   |
| 0.0           | 27.0  | 5940  | 1.6914          | 0.8537   |
| 0.0           | 28.0  | 6160  | 1.6963          | 0.8537   |
| 0.0           | 29.0  | 6380  | 1.7007          | 0.8537   |
| 0.0           | 30.0  | 6600  | 1.7046          | 0.8537   |
| 0.0           | 31.0  | 6820  | 1.7081          | 0.8537   |
| 0.0           | 32.0  | 7040  | 1.7112          | 0.8537   |
| 0.0           | 33.0  | 7260  | 1.7141          | 0.8537   |
| 0.0           | 34.0  | 7480  | 1.7167          | 0.8537   |
| 0.0           | 35.0  | 7700  | 1.7191          | 0.8537   |
| 0.0           | 36.0  | 7920  | 1.7212          | 0.8537   |
| 0.0           | 37.0  | 8140  | 1.7232          | 0.8537   |
| 0.0           | 38.0  | 8360  | 1.7249          | 0.8537   |
| 0.0           | 39.0  | 8580  | 1.7265          | 0.8537   |
| 0.0           | 40.0  | 8800  | 1.7279          | 0.8537   |
| 0.0           | 41.0  | 9020  | 1.7292          | 0.8537   |
| 0.0           | 42.0  | 9240  | 1.7303          | 0.8537   |
| 0.0           | 43.0  | 9460  | 1.7312          | 0.8537   |
| 0.0           | 44.0  | 9680  | 1.7321          | 0.8537   |
| 0.0           | 45.0  | 9900  | 1.7328          | 0.8537   |
| 0.0           | 46.0  | 10120 | 1.7333          | 0.8537   |
| 0.0           | 47.0  | 10340 | 1.7337          | 0.8537   |
| 0.0           | 48.0  | 10560 | 1.7340          | 0.8537   |
| 0.0           | 49.0  | 10780 | 1.7342          | 0.8537   |
| 0.0           | 50.0  | 11000 | 1.7342          | 0.8537   |


### 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