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# hushem_40x_deit_small_rms_001_fold3

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: 3.1579
- Accuracy: 0.7442

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2419        | 1.0   | 217   | 1.3981          | 0.2791   |
| 1.0235        | 2.0   | 434   | 1.3169          | 0.3953   |
| 0.8369        | 3.0   | 651   | 1.0743          | 0.4884   |
| 0.7963        | 4.0   | 868   | 0.6563          | 0.6977   |
| 0.7399        | 5.0   | 1085  | 1.1403          | 0.4651   |
| 0.591         | 6.0   | 1302  | 0.6390          | 0.7209   |
| 0.4772        | 7.0   | 1519  | 0.8818          | 0.6047   |
| 0.4582        | 8.0   | 1736  | 0.8295          | 0.6744   |
| 0.4273        | 9.0   | 1953  | 1.1233          | 0.4884   |
| 0.3402        | 10.0  | 2170  | 0.8028          | 0.7442   |
| 0.3174        | 11.0  | 2387  | 1.2880          | 0.5581   |
| 0.2909        | 12.0  | 2604  | 1.5844          | 0.6512   |
| 0.2204        | 13.0  | 2821  | 1.1940          | 0.6977   |
| 0.2639        | 14.0  | 3038  | 1.0276          | 0.6279   |
| 0.2085        | 15.0  | 3255  | 1.7122          | 0.6512   |
| 0.1551        | 16.0  | 3472  | 1.0876          | 0.7209   |
| 0.2066        | 17.0  | 3689  | 1.4826          | 0.6279   |
| 0.1259        | 18.0  | 3906  | 1.7194          | 0.6279   |
| 0.1381        | 19.0  | 4123  | 1.1881          | 0.7442   |
| 0.0864        | 20.0  | 4340  | 2.4912          | 0.7209   |
| 0.1059        | 21.0  | 4557  | 1.6650          | 0.6977   |
| 0.0958        | 22.0  | 4774  | 1.6843          | 0.6977   |
| 0.0803        | 23.0  | 4991  | 2.0214          | 0.6279   |
| 0.0716        | 24.0  | 5208  | 2.3668          | 0.6977   |
| 0.0335        | 25.0  | 5425  | 1.8384          | 0.6279   |
| 0.0722        | 26.0  | 5642  | 1.9563          | 0.6744   |
| 0.0543        | 27.0  | 5859  | 2.2739          | 0.6744   |
| 0.024         | 28.0  | 6076  | 1.7616          | 0.6977   |
| 0.0588        | 29.0  | 6293  | 1.9807          | 0.6977   |
| 0.0731        | 30.0  | 6510  | 2.0008          | 0.6279   |
| 0.0315        | 31.0  | 6727  | 2.2264          | 0.7209   |
| 0.0084        | 32.0  | 6944  | 2.2231          | 0.7674   |
| 0.0194        | 33.0  | 7161  | 2.3580          | 0.6977   |
| 0.0559        | 34.0  | 7378  | 2.5423          | 0.7209   |
| 0.0002        | 35.0  | 7595  | 2.6899          | 0.7674   |
| 0.0092        | 36.0  | 7812  | 2.7843          | 0.6744   |
| 0.0002        | 37.0  | 8029  | 2.7034          | 0.7442   |
| 0.016         | 38.0  | 8246  | 2.9844          | 0.7674   |
| 0.0006        | 39.0  | 8463  | 1.9924          | 0.8140   |
| 0.006         | 40.0  | 8680  | 2.8801          | 0.6977   |
| 0.0001        | 41.0  | 8897  | 2.7323          | 0.7674   |
| 0.0001        | 42.0  | 9114  | 3.2030          | 0.6977   |
| 0.0002        | 43.0  | 9331  | 3.6553          | 0.7674   |
| 0.0001        | 44.0  | 9548  | 2.9080          | 0.7209   |
| 0.0001        | 45.0  | 9765  | 2.8393          | 0.7442   |
| 0.0           | 46.0  | 9982  | 2.9525          | 0.7442   |
| 0.0           | 47.0  | 10199 | 3.0057          | 0.7442   |
| 0.0           | 48.0  | 10416 | 3.0880          | 0.7442   |
| 0.0           | 49.0  | 10633 | 3.1339          | 0.7442   |
| 0.0           | 50.0  | 10850 | 3.1579          | 0.7442   |


### 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