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# hushem_40x_beit_large_adamax_00001_fold5

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: 0.3633
- Accuracy: 0.9268

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0116        | 1.0   | 220   | 0.3464          | 0.8780   |
| 0.0008        | 2.0   | 440   | 0.2183          | 0.9512   |
| 0.0009        | 3.0   | 660   | 0.2250          | 0.9268   |
| 0.0006        | 4.0   | 880   | 0.2906          | 0.9268   |
| 0.0001        | 5.0   | 1100  | 0.3626          | 0.9268   |
| 0.0004        | 6.0   | 1320  | 0.2649          | 0.9512   |
| 0.0           | 7.0   | 1540  | 0.4436          | 0.8780   |
| 0.0004        | 8.0   | 1760  | 0.4765          | 0.9024   |
| 0.0001        | 9.0   | 1980  | 0.4469          | 0.9024   |
| 0.0           | 10.0  | 2200  | 0.4327          | 0.8780   |
| 0.0           | 11.0  | 2420  | 0.4850          | 0.9268   |
| 0.0           | 12.0  | 2640  | 0.4853          | 0.8780   |
| 0.0           | 13.0  | 2860  | 0.5574          | 0.8537   |
| 0.0           | 14.0  | 3080  | 0.5001          | 0.9024   |
| 0.0           | 15.0  | 3300  | 0.4709          | 0.8537   |
| 0.0           | 16.0  | 3520  | 0.6659          | 0.8293   |
| 0.0           | 17.0  | 3740  | 0.8132          | 0.8293   |
| 0.0           | 18.0  | 3960  | 0.7367          | 0.8780   |
| 0.0005        | 19.0  | 4180  | 0.2607          | 0.9512   |
| 0.0           | 20.0  | 4400  | 0.3217          | 0.9512   |
| 0.0           | 21.0  | 4620  | 0.2845          | 0.9512   |
| 0.0           | 22.0  | 4840  | 0.5419          | 0.8780   |
| 0.0           | 23.0  | 5060  | 0.4106          | 0.9024   |
| 0.0           | 24.0  | 5280  | 0.3477          | 0.9024   |
| 0.0           | 25.0  | 5500  | 0.4515          | 0.8780   |
| 0.0           | 26.0  | 5720  | 0.3857          | 0.9024   |
| 0.0           | 27.0  | 5940  | 0.4374          | 0.9024   |
| 0.0           | 28.0  | 6160  | 0.5116          | 0.8780   |
| 0.0           | 29.0  | 6380  | 0.6248          | 0.8537   |
| 0.0           | 30.0  | 6600  | 0.5380          | 0.8780   |
| 0.0           | 31.0  | 6820  | 0.5231          | 0.8780   |
| 0.0           | 32.0  | 7040  | 0.5186          | 0.8780   |
| 0.0           | 33.0  | 7260  | 0.4301          | 0.9024   |
| 0.0           | 34.0  | 7480  | 0.4552          | 0.9024   |
| 0.0           | 35.0  | 7700  | 0.4309          | 0.9024   |
| 0.0           | 36.0  | 7920  | 0.5631          | 0.8780   |
| 0.0           | 37.0  | 8140  | 0.5187          | 0.8780   |
| 0.0           | 38.0  | 8360  | 0.3960          | 0.9268   |
| 0.0           | 39.0  | 8580  | 0.5497          | 0.9024   |
| 0.0           | 40.0  | 8800  | 0.4890          | 0.9024   |
| 0.0           | 41.0  | 9020  | 0.3987          | 0.9268   |
| 0.0           | 42.0  | 9240  | 0.4184          | 0.9268   |
| 0.0           | 43.0  | 9460  | 0.3286          | 0.9512   |
| 0.0           | 44.0  | 9680  | 0.3483          | 0.9268   |
| 0.0           | 45.0  | 9900  | 0.3614          | 0.9268   |
| 0.0           | 46.0  | 10120 | 0.3697          | 0.9268   |
| 0.0           | 47.0  | 10340 | 0.3577          | 0.9512   |
| 0.0           | 48.0  | 10560 | 0.3575          | 0.9512   |
| 0.0           | 49.0  | 10780 | 0.3626          | 0.9268   |
| 0.0           | 50.0  | 11000 | 0.3633          | 0.9268   |


### 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