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# hushem_5x_beit_base_adamax_00001_fold5

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: 0.6249
- Accuracy: 0.8049

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2175        | 1.0   | 28   | 1.0638          | 0.5610   |
| 0.735         | 2.0   | 56   | 0.7985          | 0.6585   |
| 0.4163        | 3.0   | 84   | 0.6796          | 0.7561   |
| 0.279         | 4.0   | 112  | 0.5555          | 0.7805   |
| 0.1477        | 5.0   | 140  | 0.5113          | 0.7805   |
| 0.1105        | 6.0   | 168  | 0.4149          | 0.8049   |
| 0.0639        | 7.0   | 196  | 0.4515          | 0.8049   |
| 0.0449        | 8.0   | 224  | 0.4623          | 0.8049   |
| 0.0253        | 9.0   | 252  | 0.4728          | 0.8049   |
| 0.0316        | 10.0  | 280  | 0.4972          | 0.8049   |
| 0.0123        | 11.0  | 308  | 0.4732          | 0.8049   |
| 0.0128        | 12.0  | 336  | 0.4924          | 0.8049   |
| 0.0101        | 13.0  | 364  | 0.4570          | 0.8049   |
| 0.0111        | 14.0  | 392  | 0.4394          | 0.8049   |
| 0.0107        | 15.0  | 420  | 0.4434          | 0.8293   |
| 0.0064        | 16.0  | 448  | 0.5061          | 0.8049   |
| 0.0038        | 17.0  | 476  | 0.4264          | 0.8049   |
| 0.0038        | 18.0  | 504  | 0.4542          | 0.8049   |
| 0.0106        | 19.0  | 532  | 0.5345          | 0.8049   |
| 0.0043        | 20.0  | 560  | 0.5084          | 0.8049   |
| 0.0022        | 21.0  | 588  | 0.5182          | 0.8049   |
| 0.0136        | 22.0  | 616  | 0.4661          | 0.8049   |
| 0.005         | 23.0  | 644  | 0.4938          | 0.8293   |
| 0.0094        | 24.0  | 672  | 0.5151          | 0.8293   |
| 0.0106        | 25.0  | 700  | 0.5393          | 0.8049   |
| 0.0023        | 26.0  | 728  | 0.5196          | 0.8293   |
| 0.0018        | 27.0  | 756  | 0.5228          | 0.8293   |
| 0.0039        | 28.0  | 784  | 0.5509          | 0.8049   |
| 0.002         | 29.0  | 812  | 0.5472          | 0.8049   |
| 0.0023        | 30.0  | 840  | 0.5687          | 0.8049   |
| 0.0017        | 31.0  | 868  | 0.5888          | 0.8049   |
| 0.0023        | 32.0  | 896  | 0.5665          | 0.8049   |
| 0.0021        | 33.0  | 924  | 0.5478          | 0.8049   |
| 0.002         | 34.0  | 952  | 0.5621          | 0.8049   |
| 0.0027        | 35.0  | 980  | 0.5915          | 0.8049   |
| 0.0012        | 36.0  | 1008 | 0.6391          | 0.8049   |
| 0.0008        | 37.0  | 1036 | 0.6817          | 0.8049   |
| 0.0029        | 38.0  | 1064 | 0.6733          | 0.8049   |
| 0.0009        | 39.0  | 1092 | 0.6240          | 0.8049   |
| 0.0018        | 40.0  | 1120 | 0.6057          | 0.8049   |
| 0.0019        | 41.0  | 1148 | 0.6204          | 0.8049   |
| 0.0009        | 42.0  | 1176 | 0.6350          | 0.8049   |
| 0.0017        | 43.0  | 1204 | 0.6368          | 0.8049   |
| 0.006         | 44.0  | 1232 | 0.6329          | 0.8049   |
| 0.0022        | 45.0  | 1260 | 0.6324          | 0.8049   |
| 0.0014        | 46.0  | 1288 | 0.6308          | 0.8049   |
| 0.0013        | 47.0  | 1316 | 0.6209          | 0.8049   |
| 0.0019        | 48.0  | 1344 | 0.6248          | 0.8049   |
| 0.0007        | 49.0  | 1372 | 0.6249          | 0.8049   |
| 0.0012        | 50.0  | 1400 | 0.6249          | 0.8049   |


### 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