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# hushem_40x_beit_large_adamax_001_fold2

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4537
- Accuracy: 0.6889

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3184        | 1.0   | 215   | 1.1233          | 0.7333   |
| 0.1436        | 2.0   | 430   | 1.6198          | 0.6889   |
| 0.047         | 3.0   | 645   | 1.8592          | 0.6667   |
| 0.0527        | 4.0   | 860   | 1.5842          | 0.7111   |
| 0.0463        | 5.0   | 1075  | 2.7619          | 0.6889   |
| 0.0137        | 6.0   | 1290  | 1.4680          | 0.7556   |
| 0.0665        | 7.0   | 1505  | 2.2491          | 0.6889   |
| 0.0121        | 8.0   | 1720  | 1.7706          | 0.7556   |
| 0.0005        | 9.0   | 1935  | 2.1035          | 0.7556   |
| 0.0192        | 10.0  | 2150  | 3.0002          | 0.6889   |
| 0.02          | 11.0  | 2365  | 2.1406          | 0.6667   |
| 0.011         | 12.0  | 2580  | 2.2828          | 0.6667   |
| 0.0346        | 13.0  | 2795  | 2.5178          | 0.6667   |
| 0.0045        | 14.0  | 3010  | 2.0578          | 0.7333   |
| 0.0021        | 15.0  | 3225  | 1.4918          | 0.7556   |
| 0.0002        | 16.0  | 3440  | 2.6023          | 0.7111   |
| 0.0007        | 17.0  | 3655  | 2.4242          | 0.7111   |
| 0.0019        | 18.0  | 3870  | 2.8391          | 0.6667   |
| 0.0005        | 19.0  | 4085  | 2.9921          | 0.7556   |
| 0.0           | 20.0  | 4300  | 3.1529          | 0.6667   |
| 0.0           | 21.0  | 4515  | 2.7412          | 0.7556   |
| 0.0           | 22.0  | 4730  | 2.8583          | 0.7333   |
| 0.0           | 23.0  | 4945  | 2.9971          | 0.7333   |
| 0.0           | 24.0  | 5160  | 3.0142          | 0.7556   |
| 0.0           | 25.0  | 5375  | 3.0328          | 0.7556   |
| 0.0           | 26.0  | 5590  | 3.0307          | 0.7778   |
| 0.0           | 27.0  | 5805  | 3.2285          | 0.7556   |
| 0.0           | 28.0  | 6020  | 3.2719          | 0.7111   |
| 0.0           | 29.0  | 6235  | 2.7270          | 0.7778   |
| 0.0           | 30.0  | 6450  | 3.4979          | 0.7111   |
| 0.0           | 31.0  | 6665  | 3.4752          | 0.7333   |
| 0.0           | 32.0  | 6880  | 3.4952          | 0.7333   |
| 0.0           | 33.0  | 7095  | 3.5111          | 0.7333   |
| 0.0           | 34.0  | 7310  | 3.5230          | 0.7333   |
| 0.0           | 35.0  | 7525  | 3.5422          | 0.7333   |
| 0.0           | 36.0  | 7740  | 3.5606          | 0.7333   |
| 0.0           | 37.0  | 7955  | 3.5754          | 0.7333   |
| 0.0           | 38.0  | 8170  | 3.5859          | 0.7333   |
| 0.0           | 39.0  | 8385  | 3.5773          | 0.7333   |
| 0.0           | 40.0  | 8600  | 4.7039          | 0.6      |
| 0.0           | 41.0  | 8815  | 4.7831          | 0.6      |
| 0.0           | 42.0  | 9030  | 4.4812          | 0.6667   |
| 0.0           | 43.0  | 9245  | 4.4224          | 0.6889   |
| 0.0           | 44.0  | 9460  | 4.4294          | 0.6889   |
| 0.0           | 45.0  | 9675  | 4.4285          | 0.6889   |
| 0.0           | 46.0  | 9890  | 4.4304          | 0.6889   |
| 0.0           | 47.0  | 10105 | 4.4476          | 0.6889   |
| 0.0           | 48.0  | 10320 | 4.4513          | 0.6889   |
| 0.0           | 49.0  | 10535 | 4.4531          | 0.6889   |
| 0.0           | 50.0  | 10750 | 4.4537          | 0.6889   |


### 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