
<!-- 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_beit_base_rms_0001_fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 6.9592
- Accuracy: 0.5111

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3984        | 1.0   | 27   | 1.3816          | 0.2889   |
| 1.3107        | 2.0   | 54   | 1.6609          | 0.2889   |
| 1.229         | 3.0   | 81   | 1.5449          | 0.2889   |
| 1.3814        | 4.0   | 108  | 1.6341          | 0.2889   |
| 1.2031        | 5.0   | 135  | 1.4184          | 0.2667   |
| 1.1619        | 6.0   | 162  | 1.4603          | 0.2889   |
| 1.1757        | 7.0   | 189  | 1.4200          | 0.2889   |
| 1.1575        | 8.0   | 216  | 1.3581          | 0.2889   |
| 1.0419        | 9.0   | 243  | 1.5164          | 0.4      |
| 1.0334        | 10.0  | 270  | 1.3939          | 0.4889   |
| 0.799         | 11.0  | 297  | 1.4216          | 0.5333   |
| 0.7589        | 12.0  | 324  | 1.5018          | 0.5111   |
| 0.7466        | 13.0  | 351  | 1.2714          | 0.3778   |
| 0.7077        | 14.0  | 378  | 1.2899          | 0.4      |
| 0.7022        | 15.0  | 405  | 1.4427          | 0.3333   |
| 0.6019        | 16.0  | 432  | 1.5793          | 0.4      |
| 0.6413        | 17.0  | 459  | 1.5251          | 0.3111   |
| 0.6003        | 18.0  | 486  | 2.0148          | 0.4889   |
| 0.5924        | 19.0  | 513  | 2.2670          | 0.4889   |
| 0.5357        | 20.0  | 540  | 2.0323          | 0.3556   |
| 0.5196        | 21.0  | 567  | 2.5285          | 0.4889   |
| 0.5137        | 22.0  | 594  | 3.7709          | 0.4222   |
| 0.4488        | 23.0  | 621  | 3.1001          | 0.5111   |
| 0.4667        | 24.0  | 648  | 2.9452          | 0.4      |
| 0.3277        | 25.0  | 675  | 2.8861          | 0.4667   |
| 0.3619        | 26.0  | 702  | 3.3939          | 0.5111   |
| 0.3379        | 27.0  | 729  | 3.5247          | 0.5333   |
| 0.2572        | 28.0  | 756  | 4.2104          | 0.5111   |
| 0.2257        | 29.0  | 783  | 3.4821          | 0.4889   |
| 0.2189        | 30.0  | 810  | 3.8860          | 0.4667   |
| 0.1431        | 31.0  | 837  | 5.2772          | 0.4667   |
| 0.2402        | 32.0  | 864  | 6.2470          | 0.4222   |
| 0.122         | 33.0  | 891  | 5.2693          | 0.4      |
| 0.2017        | 34.0  | 918  | 6.0732          | 0.5111   |
| 0.0844        | 35.0  | 945  | 6.0091          | 0.5556   |
| 0.1316        | 36.0  | 972  | 6.1584          | 0.4889   |
| 0.0377        | 37.0  | 999  | 7.3245          | 0.4889   |
| 0.1128        | 38.0  | 1026 | 6.6950          | 0.4444   |
| 0.0551        | 39.0  | 1053 | 7.0821          | 0.5111   |
| 0.0382        | 40.0  | 1080 | 7.5961          | 0.4889   |
| 0.0547        | 41.0  | 1107 | 6.2914          | 0.5111   |
| 0.0128        | 42.0  | 1134 | 6.4101          | 0.4889   |
| 0.0359        | 43.0  | 1161 | 6.6377          | 0.5111   |
| 0.004         | 44.0  | 1188 | 6.6707          | 0.4889   |
| 0.0224        | 45.0  | 1215 | 7.0078          | 0.4889   |
| 0.0292        | 46.0  | 1242 | 6.9800          | 0.4889   |
| 0.0156        | 47.0  | 1269 | 6.9010          | 0.4889   |
| 0.0096        | 48.0  | 1296 | 6.9583          | 0.5111   |
| 0.0108        | 49.0  | 1323 | 6.9592          | 0.5111   |
| 0.0394        | 50.0  | 1350 | 6.9592          | 0.5111   |


### 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