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# hushem_40x_deit_base_rms_001_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: 8.5594
- Accuracy: 0.5778

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1732        | 1.0   | 215   | 1.0108          | 0.4667   |
| 0.7763        | 2.0   | 430   | 1.2138          | 0.5333   |
| 0.7021        | 3.0   | 645   | 1.2446          | 0.4      |
| 0.6002        | 4.0   | 860   | 1.7707          | 0.4444   |
| 0.4988        | 5.0   | 1075  | 2.1116          | 0.4667   |
| 0.4269        | 6.0   | 1290  | 2.3849          | 0.5556   |
| 0.3366        | 7.0   | 1505  | 2.4322          | 0.5556   |
| 0.2961        | 8.0   | 1720  | 3.2646          | 0.5556   |
| 0.2377        | 9.0   | 1935  | 3.1438          | 0.5333   |
| 0.2435        | 10.0  | 2150  | 3.6031          | 0.5778   |
| 0.2593        | 11.0  | 2365  | 3.5951          | 0.4889   |
| 0.1482        | 12.0  | 2580  | 3.8372          | 0.5111   |
| 0.1871        | 13.0  | 2795  | 3.7490          | 0.6222   |
| 0.1246        | 14.0  | 3010  | 3.7977          | 0.5333   |
| 0.166         | 15.0  | 3225  | 3.7321          | 0.5778   |
| 0.1672        | 16.0  | 3440  | 4.6413          | 0.4889   |
| 0.1752        | 17.0  | 3655  | 4.9330          | 0.5556   |
| 0.1214        | 18.0  | 3870  | 4.3615          | 0.5556   |
| 0.0488        | 19.0  | 4085  | 4.4231          | 0.5111   |
| 0.1336        | 20.0  | 4300  | 4.4451          | 0.5778   |
| 0.1002        | 21.0  | 4515  | 3.7455          | 0.5778   |
| 0.0734        | 22.0  | 4730  | 4.4970          | 0.5556   |
| 0.0322        | 23.0  | 4945  | 4.8990          | 0.5333   |
| 0.214         | 24.0  | 5160  | 5.1865          | 0.5778   |
| 0.1242        | 25.0  | 5375  | 5.0088          | 0.5333   |
| 0.0033        | 26.0  | 5590  | 4.9606          | 0.5556   |
| 0.0333        | 27.0  | 5805  | 4.4063          | 0.5778   |
| 0.0592        | 28.0  | 6020  | 4.1719          | 0.5556   |
| 0.0444        | 29.0  | 6235  | 6.2342          | 0.5111   |
| 0.0039        | 30.0  | 6450  | 5.9834          | 0.5333   |
| 0.003         | 31.0  | 6665  | 6.2329          | 0.5333   |
| 0.0008        | 32.0  | 6880  | 6.2499          | 0.6      |
| 0.1078        | 33.0  | 7095  | 5.2542          | 0.6222   |
| 0.0258        | 34.0  | 7310  | 6.7980          | 0.4889   |
| 0.0052        | 35.0  | 7525  | 6.6849          | 0.5333   |
| 0.0003        | 36.0  | 7740  | 6.1342          | 0.5556   |
| 0.0005        | 37.0  | 7955  | 5.4920          | 0.5778   |
| 0.0004        | 38.0  | 8170  | 5.3684          | 0.5778   |
| 0.0148        | 39.0  | 8385  | 5.3551          | 0.5556   |
| 0.0054        | 40.0  | 8600  | 7.4300          | 0.5111   |
| 0.0           | 41.0  | 8815  | 6.8539          | 0.5556   |
| 0.0           | 42.0  | 9030  | 6.8688          | 0.5556   |
| 0.0           | 43.0  | 9245  | 7.1702          | 0.5778   |
| 0.0           | 44.0  | 9460  | 7.4631          | 0.5778   |
| 0.0           | 45.0  | 9675  | 7.7338          | 0.5778   |
| 0.0           | 46.0  | 9890  | 7.9825          | 0.5778   |
| 0.0           | 47.0  | 10105 | 8.2172          | 0.5778   |
| 0.0           | 48.0  | 10320 | 8.4047          | 0.5778   |
| 0.0           | 49.0  | 10535 | 8.5267          | 0.5778   |
| 0.0           | 50.0  | 10750 | 8.5594          | 0.5778   |


### 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