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# hushem_40x_deit_small_rms_001_fold5

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: 1.6080
- Accuracy: 0.7805

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4202        | 1.0   | 220   | 1.3858          | 0.2439   |
| 1.4846        | 2.0   | 440   | 1.3050          | 0.3659   |
| 1.213         | 3.0   | 660   | 1.2527          | 0.3659   |
| 1.2436        | 4.0   | 880   | 1.2166          | 0.3659   |
| 1.1042        | 5.0   | 1100  | 1.0859          | 0.4878   |
| 1.1247        | 6.0   | 1320  | 1.0109          | 0.5854   |
| 1.1005        | 7.0   | 1540  | 1.0680          | 0.4634   |
| 1.0292        | 8.0   | 1760  | 0.9693          | 0.5366   |
| 0.9154        | 9.0   | 1980  | 1.0620          | 0.6829   |
| 0.8944        | 10.0  | 2200  | 0.7963          | 0.6585   |
| 0.9136        | 11.0  | 2420  | 1.0510          | 0.5854   |
| 0.8882        | 12.0  | 2640  | 0.9455          | 0.6098   |
| 0.8527        | 13.0  | 2860  | 0.7251          | 0.6098   |
| 0.7429        | 14.0  | 3080  | 0.7653          | 0.7805   |
| 0.6936        | 15.0  | 3300  | 0.7806          | 0.7561   |
| 0.7049        | 16.0  | 3520  | 1.3071          | 0.6585   |
| 0.6294        | 17.0  | 3740  | 0.5950          | 0.7561   |
| 0.6472        | 18.0  | 3960  | 0.4686          | 0.7561   |
| 0.6452        | 19.0  | 4180  | 0.5722          | 0.7561   |
| 0.5301        | 20.0  | 4400  | 0.8370          | 0.6341   |
| 0.5967        | 21.0  | 4620  | 0.5708          | 0.8537   |
| 0.4666        | 22.0  | 4840  | 0.3950          | 0.8293   |
| 0.5239        | 23.0  | 5060  | 0.5273          | 0.8049   |
| 0.5888        | 24.0  | 5280  | 0.4686          | 0.7561   |
| 0.5034        | 25.0  | 5500  | 0.5275          | 0.7561   |
| 0.5755        | 26.0  | 5720  | 0.4866          | 0.7805   |
| 0.5913        | 27.0  | 5940  | 0.8503          | 0.7805   |
| 0.405         | 28.0  | 6160  | 0.5132          | 0.8049   |
| 0.4508        | 29.0  | 6380  | 0.7683          | 0.7805   |
| 0.4334        | 30.0  | 6600  | 0.7092          | 0.8293   |
| 0.4219        | 31.0  | 6820  | 0.5130          | 0.7561   |
| 0.4182        | 32.0  | 7040  | 0.5153          | 0.8293   |
| 0.308         | 33.0  | 7260  | 0.5501          | 0.7561   |
| 0.3445        | 34.0  | 7480  | 0.6037          | 0.8049   |
| 0.2565        | 35.0  | 7700  | 0.5862          | 0.7805   |
| 0.2803        | 36.0  | 7920  | 0.7253          | 0.7805   |
| 0.3045        | 37.0  | 8140  | 0.9133          | 0.6829   |
| 0.2202        | 38.0  | 8360  | 0.8750          | 0.7073   |
| 0.222         | 39.0  | 8580  | 0.5361          | 0.7805   |
| 0.1816        | 40.0  | 8800  | 1.1395          | 0.7317   |
| 0.2213        | 41.0  | 9020  | 0.9746          | 0.7561   |
| 0.16          | 42.0  | 9240  | 1.0585          | 0.7317   |
| 0.1084        | 43.0  | 9460  | 0.8736          | 0.7073   |
| 0.1243        | 44.0  | 9680  | 1.1686          | 0.8049   |
| 0.1009        | 45.0  | 9900  | 0.9862          | 0.7561   |
| 0.096         | 46.0  | 10120 | 1.4994          | 0.6829   |
| 0.089         | 47.0  | 10340 | 1.4415          | 0.7561   |
| 0.0473        | 48.0  | 10560 | 1.6197          | 0.7805   |
| 0.0266        | 49.0  | 10780 | 1.5765          | 0.7805   |
| 0.0418        | 50.0  | 11000 | 1.6080          | 0.7805   |


### 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