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# hushem_40x_deit_base_adamax_001_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: 0.4744
- Accuracy: 0.9024

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2741        | 1.0   | 220   | 0.7783          | 0.7317   |
| 0.1315        | 2.0   | 440   | 0.8361          | 0.8293   |
| 0.0434        | 3.0   | 660   | 1.2093          | 0.7317   |
| 0.0894        | 4.0   | 880   | 0.3662          | 0.9024   |
| 0.0527        | 5.0   | 1100  | 0.4869          | 0.9024   |
| 0.0501        | 6.0   | 1320  | 0.3025          | 0.9512   |
| 0.001         | 7.0   | 1540  | 0.5424          | 0.9024   |
| 0.023         | 8.0   | 1760  | 0.6857          | 0.9024   |
| 0.0256        | 9.0   | 1980  | 1.0120          | 0.8780   |
| 0.0166        | 10.0  | 2200  | 0.5130          | 0.8780   |
| 0.0004        | 11.0  | 2420  | 0.4559          | 0.8780   |
| 0.0217        | 12.0  | 2640  | 1.2147          | 0.7805   |
| 0.0002        | 13.0  | 2860  | 0.2445          | 0.9268   |
| 0.0           | 14.0  | 3080  | 0.2240          | 0.9268   |
| 0.0           | 15.0  | 3300  | 0.2460          | 0.9268   |
| 0.0           | 16.0  | 3520  | 0.2550          | 0.9268   |
| 0.0           | 17.0  | 3740  | 0.2642          | 0.9268   |
| 0.0           | 18.0  | 3960  | 0.2728          | 0.9268   |
| 0.0           | 19.0  | 4180  | 0.2816          | 0.9268   |
| 0.0           | 20.0  | 4400  | 0.2891          | 0.9268   |
| 0.0           | 21.0  | 4620  | 0.2969          | 0.9268   |
| 0.0           | 22.0  | 4840  | 0.3042          | 0.9268   |
| 0.0           | 23.0  | 5060  | 0.3121          | 0.9268   |
| 0.0           | 24.0  | 5280  | 0.3198          | 0.9268   |
| 0.0           | 25.0  | 5500  | 0.3281          | 0.9268   |
| 0.0           | 26.0  | 5720  | 0.3364          | 0.9268   |
| 0.0           | 27.0  | 5940  | 0.3437          | 0.9268   |
| 0.0           | 28.0  | 6160  | 0.3515          | 0.9268   |
| 0.0           | 29.0  | 6380  | 0.3592          | 0.9268   |
| 0.0           | 30.0  | 6600  | 0.3667          | 0.9268   |
| 0.0           | 31.0  | 6820  | 0.3741          | 0.9268   |
| 0.0           | 32.0  | 7040  | 0.3811          | 0.9268   |
| 0.0           | 33.0  | 7260  | 0.3879          | 0.9268   |
| 0.0           | 34.0  | 7480  | 0.3952          | 0.9268   |
| 0.0           | 35.0  | 7700  | 0.4021          | 0.9268   |
| 0.0           | 36.0  | 7920  | 0.4093          | 0.9268   |
| 0.0           | 37.0  | 8140  | 0.4163          | 0.9268   |
| 0.0           | 38.0  | 8360  | 0.4226          | 0.9268   |
| 0.0           | 39.0  | 8580  | 0.4295          | 0.9268   |
| 0.0           | 40.0  | 8800  | 0.4358          | 0.9268   |
| 0.0           | 41.0  | 9020  | 0.4415          | 0.9268   |
| 0.0           | 42.0  | 9240  | 0.4471          | 0.9268   |
| 0.0           | 43.0  | 9460  | 0.4531          | 0.9268   |
| 0.0           | 44.0  | 9680  | 0.4575          | 0.9268   |
| 0.0           | 45.0  | 9900  | 0.4619          | 0.9268   |
| 0.0           | 46.0  | 10120 | 0.4664          | 0.9268   |
| 0.0           | 47.0  | 10340 | 0.4696          | 0.9268   |
| 0.0           | 48.0  | 10560 | 0.4724          | 0.9024   |
| 0.0           | 49.0  | 10780 | 0.4740          | 0.9024   |
| 0.0           | 50.0  | 11000 | 0.4744          | 0.9024   |


### 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