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# hushem_5x_beit_base_adamax_0001_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: 0.9920
- Accuracy: 0.8293

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.641         | 1.0   | 28   | 0.5863          | 0.7317   |
| 0.1363        | 2.0   | 56   | 0.5085          | 0.8049   |
| 0.0403        | 3.0   | 84   | 0.8067          | 0.8049   |
| 0.0158        | 4.0   | 112  | 0.6196          | 0.7805   |
| 0.0024        | 5.0   | 140  | 0.5093          | 0.9024   |
| 0.0017        | 6.0   | 168  | 0.8498          | 0.8293   |
| 0.0016        | 7.0   | 196  | 0.8351          | 0.8537   |
| 0.0006        | 8.0   | 224  | 0.8986          | 0.8293   |
| 0.0004        | 9.0   | 252  | 0.5488          | 0.8780   |
| 0.0018        | 10.0  | 280  | 0.6108          | 0.8780   |
| 0.0004        | 11.0  | 308  | 0.7112          | 0.8537   |
| 0.0001        | 12.0  | 336  | 0.7806          | 0.8537   |
| 0.0001        | 13.0  | 364  | 0.8893          | 0.8780   |
| 0.0001        | 14.0  | 392  | 0.9596          | 0.8293   |
| 0.005         | 15.0  | 420  | 0.6813          | 0.9024   |
| 0.0001        | 16.0  | 448  | 0.9535          | 0.7561   |
| 0.0002        | 17.0  | 476  | 0.6993          | 0.8537   |
| 0.0001        | 18.0  | 504  | 0.6415          | 0.8537   |
| 0.0001        | 19.0  | 532  | 0.6851          | 0.8293   |
| 0.0           | 20.0  | 560  | 0.6721          | 0.8537   |
| 0.0001        | 21.0  | 588  | 0.6658          | 0.8537   |
| 0.0001        | 22.0  | 616  | 0.6422          | 0.8537   |
| 0.0           | 23.0  | 644  | 0.6457          | 0.8537   |
| 0.0001        | 24.0  | 672  | 0.6659          | 0.8537   |
| 0.0001        | 25.0  | 700  | 0.6825          | 0.8537   |
| 0.0           | 26.0  | 728  | 0.7334          | 0.8293   |
| 0.0           | 27.0  | 756  | 0.7447          | 0.8293   |
| 0.0           | 28.0  | 784  | 0.7524          | 0.8293   |
| 0.0001        | 29.0  | 812  | 0.7681          | 0.8293   |
| 0.0           | 30.0  | 840  | 0.7829          | 0.8293   |
| 0.0001        | 31.0  | 868  | 0.9622          | 0.8293   |
| 0.0002        | 32.0  | 896  | 1.1091          | 0.8293   |
| 0.0           | 33.0  | 924  | 1.0337          | 0.8293   |
| 0.0           | 34.0  | 952  | 0.9846          | 0.8293   |
| 0.0           | 35.0  | 980  | 0.9615          | 0.8293   |
| 0.0001        | 36.0  | 1008 | 0.9612          | 0.8293   |
| 0.0001        | 37.0  | 1036 | 0.9494          | 0.8293   |
| 0.0001        | 38.0  | 1064 | 0.9364          | 0.8293   |
| 0.0           | 39.0  | 1092 | 0.9014          | 0.8293   |
| 0.0002        | 40.0  | 1120 | 0.8887          | 0.8293   |
| 0.0001        | 41.0  | 1148 | 0.9321          | 0.8293   |
| 0.0           | 42.0  | 1176 | 0.9557          | 0.8293   |
| 0.0           | 43.0  | 1204 | 1.0018          | 0.8293   |
| 0.0           | 44.0  | 1232 | 1.0026          | 0.8293   |
| 0.0006        | 45.0  | 1260 | 0.9880          | 0.8293   |
| 0.0001        | 46.0  | 1288 | 0.9929          | 0.8293   |
| 0.0001        | 47.0  | 1316 | 0.9924          | 0.8293   |
| 0.0           | 48.0  | 1344 | 0.9920          | 0.8293   |
| 0.0           | 49.0  | 1372 | 0.9920          | 0.8293   |
| 0.0           | 50.0  | 1400 | 0.9920          | 0.8293   |


### 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