
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_5x_deit_small_adamax_001_fold4

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: 2.6296
- Accuracy: 0.7143

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4114        | 1.0   | 28   | 1.1807          | 0.5238   |
| 1.2764        | 2.0   | 56   | 0.9991          | 0.5      |
| 0.9708        | 3.0   | 84   | 0.8093          | 0.5952   |
| 0.8975        | 4.0   | 112  | 0.7127          | 0.7143   |
| 0.8745        | 5.0   | 140  | 0.6175          | 0.7857   |
| 0.8263        | 6.0   | 168  | 0.5662          | 0.7857   |
| 0.7023        | 7.0   | 196  | 0.9422          | 0.4762   |
| 0.739         | 8.0   | 224  | 1.0785          | 0.6667   |
| 0.6219        | 9.0   | 252  | 0.7234          | 0.7381   |
| 0.5557        | 10.0  | 280  | 0.9010          | 0.6429   |
| 0.5536        | 11.0  | 308  | 0.8428          | 0.6905   |
| 0.4341        | 12.0  | 336  | 1.4219          | 0.5952   |
| 0.4008        | 13.0  | 364  | 1.0252          | 0.6190   |
| 0.3661        | 14.0  | 392  | 0.9782          | 0.6667   |
| 0.2255        | 15.0  | 420  | 1.0569          | 0.6905   |
| 0.1906        | 16.0  | 448  | 1.2300          | 0.7381   |
| 0.1975        | 17.0  | 476  | 1.3396          | 0.6905   |
| 0.1887        | 18.0  | 504  | 1.2504          | 0.6905   |
| 0.1207        | 19.0  | 532  | 1.3305          | 0.6905   |
| 0.0442        | 20.0  | 560  | 1.3516          | 0.7143   |
| 0.0689        | 21.0  | 588  | 1.7387          | 0.7143   |
| 0.0525        | 22.0  | 616  | 1.7134          | 0.6667   |
| 0.0339        | 23.0  | 644  | 1.8502          | 0.7381   |
| 0.0226        | 24.0  | 672  | 2.0846          | 0.7143   |
| 0.0026        | 25.0  | 700  | 2.2517          | 0.6905   |
| 0.0003        | 26.0  | 728  | 2.4690          | 0.6667   |
| 0.0231        | 27.0  | 756  | 2.7345          | 0.7143   |
| 0.0001        | 28.0  | 784  | 2.7167          | 0.7381   |
| 0.0001        | 29.0  | 812  | 2.5959          | 0.7143   |
| 0.0033        | 30.0  | 840  | 2.4481          | 0.7143   |
| 0.0096        | 31.0  | 868  | 2.5344          | 0.6905   |
| 0.0001        | 32.0  | 896  | 2.5507          | 0.7143   |
| 0.0           | 33.0  | 924  | 2.5703          | 0.7143   |
| 0.0           | 34.0  | 952  | 2.5803          | 0.7143   |
| 0.0           | 35.0  | 980  | 2.5893          | 0.7143   |
| 0.0           | 36.0  | 1008 | 2.5965          | 0.7143   |
| 0.0           | 37.0  | 1036 | 2.6022          | 0.7143   |
| 0.0           | 38.0  | 1064 | 2.6075          | 0.7143   |
| 0.0           | 39.0  | 1092 | 2.6116          | 0.7143   |
| 0.0           | 40.0  | 1120 | 2.6157          | 0.7143   |
| 0.0           | 41.0  | 1148 | 2.6188          | 0.7143   |
| 0.0           | 42.0  | 1176 | 2.6214          | 0.7143   |
| 0.0           | 43.0  | 1204 | 2.6241          | 0.7143   |
| 0.0           | 44.0  | 1232 | 2.6260          | 0.7143   |
| 0.0           | 45.0  | 1260 | 2.6276          | 0.7143   |
| 0.0           | 46.0  | 1288 | 2.6284          | 0.7143   |
| 0.0           | 47.0  | 1316 | 2.6292          | 0.7143   |
| 0.0           | 48.0  | 1344 | 2.6296          | 0.7143   |
| 0.0           | 49.0  | 1372 | 2.6296          | 0.7143   |
| 0.0           | 50.0  | 1400 | 2.6296          | 0.7143   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

01_normal 02_tapered 03_pyriform 04_amorphous