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# hushem_40x_beit_large_adamax_001_fold1

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: 3.2476
- Accuracy: 0.7333

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3238        | 1.0   | 215   | 0.6915          | 0.7333   |
| 0.1477        | 2.0   | 430   | 1.2081          | 0.6444   |
| 0.0434        | 3.0   | 645   | 1.8202          | 0.6444   |
| 0.0459        | 4.0   | 860   | 1.9604          | 0.6222   |
| 0.0376        | 5.0   | 1075  | 0.7965          | 0.7778   |
| 0.0151        | 6.0   | 1290  | 1.6449          | 0.7111   |
| 0.0084        | 7.0   | 1505  | 2.7172          | 0.6222   |
| 0.0085        | 8.0   | 1720  | 2.4588          | 0.6667   |
| 0.0105        | 9.0   | 1935  | 3.0173          | 0.5333   |
| 0.0465        | 10.0  | 2150  | 1.5242          | 0.7778   |
| 0.0056        | 11.0  | 2365  | 2.2494          | 0.7333   |
| 0.0106        | 12.0  | 2580  | 2.3865          | 0.6889   |
| 0.0614        | 13.0  | 2795  | 1.3048          | 0.7778   |
| 0.0068        | 14.0  | 3010  | 2.7128          | 0.6889   |
| 0.0           | 15.0  | 3225  | 2.3042          | 0.7778   |
| 0.0001        | 16.0  | 3440  | 2.6333          | 0.7333   |
| 0.0483        | 17.0  | 3655  | 2.9792          | 0.7111   |
| 0.0           | 18.0  | 3870  | 2.6692          | 0.7111   |
| 0.0           | 19.0  | 4085  | 2.7990          | 0.7556   |
| 0.0           | 20.0  | 4300  | 2.7968          | 0.7333   |
| 0.0           | 21.0  | 4515  | 2.8289          | 0.7333   |
| 0.0           | 22.0  | 4730  | 2.8734          | 0.7333   |
| 0.0           | 23.0  | 4945  | 2.7220          | 0.7556   |
| 0.0742        | 24.0  | 5160  | 2.8716          | 0.7111   |
| 0.0011        | 25.0  | 5375  | 2.8927          | 0.7333   |
| 0.0           | 26.0  | 5590  | 2.8101          | 0.7333   |
| 0.0           | 27.0  | 5805  | 2.9619          | 0.7111   |
| 0.0           | 28.0  | 6020  | 3.0313          | 0.7111   |
| 0.0           | 29.0  | 6235  | 3.1395          | 0.7111   |
| 0.0           | 30.0  | 6450  | 3.4589          | 0.7111   |
| 0.0           | 31.0  | 6665  | 3.5502          | 0.6889   |
| 0.0           | 32.0  | 6880  | 3.7038          | 0.6667   |
| 0.0           | 33.0  | 7095  | 2.9949          | 0.7111   |
| 0.0           | 34.0  | 7310  | 3.0364          | 0.7111   |
| 0.0           | 35.0  | 7525  | 3.1096          | 0.7111   |
| 0.0           | 36.0  | 7740  | 3.1633          | 0.7333   |
| 0.0           | 37.0  | 7955  | 3.1868          | 0.7333   |
| 0.0           | 38.0  | 8170  | 3.2061          | 0.7333   |
| 0.0           | 39.0  | 8385  | 3.2444          | 0.7333   |
| 0.0           | 40.0  | 8600  | 3.2660          | 0.7333   |
| 0.0           | 41.0  | 8815  | 3.2861          | 0.7333   |
| 0.0           | 42.0  | 9030  | 3.3090          | 0.7333   |
| 0.0           | 43.0  | 9245  | 3.3340          | 0.7333   |
| 0.0           | 44.0  | 9460  | 3.3547          | 0.7333   |
| 0.0           | 45.0  | 9675  | 3.3742          | 0.7333   |
| 0.0           | 46.0  | 9890  | 3.3879          | 0.7333   |
| 0.0           | 47.0  | 10105 | 3.4047          | 0.7333   |
| 0.0           | 48.0  | 10320 | 3.2184          | 0.7333   |
| 0.0           | 49.0  | 10535 | 3.2219          | 0.7333   |
| 0.0           | 50.0  | 10750 | 3.2476          | 0.7333   |


### 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