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# results

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8129
- Accuracy: 0.5969

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9759        | 1.0   | 37   | 0.9392          | 0.5408   |
| 0.8313        | 2.0   | 74   | 0.8845          | 0.6122   |
| 0.8032        | 3.0   | 111  | 0.8459          | 0.6122   |
| 0.7375        | 4.0   | 148  | 0.8693          | 0.5782   |
| 0.635         | 5.0   | 185  | 0.8724          | 0.6344   |
| 0.578         | 6.0   | 222  | 0.9932          | 0.5629   |
| 0.3875        | 7.0   | 259  | 1.0738          | 0.5952   |
| 0.3544        | 8.0   | 296  | 1.1359          | 0.6156   |
| 0.407         | 9.0   | 333  | 1.3020          | 0.5493   |
| 0.2329        | 10.0  | 370  | 1.2567          | 0.6020   |
| 0.2305        | 11.0  | 407  | 1.3148          | 0.6156   |
| 0.2098        | 12.0  | 444  | 1.2928          | 0.6241   |
| 0.1595        | 13.0  | 481  | 1.5325          | 0.5629   |
| 0.1515        | 14.0  | 518  | 1.4402          | 0.6156   |
| 0.1429        | 15.0  | 555  | 1.4456          | 0.6276   |
| 0.1812        | 16.0  | 592  | 1.5088          | 0.5663   |
| 0.1169        | 17.0  | 629  | 1.6266          | 0.5850   |
| 0.1375        | 18.0  | 666  | 1.5252          | 0.6173   |
| 0.0907        | 19.0  | 703  | 1.6055          | 0.6088   |
| 0.1003        | 20.0  | 740  | 1.5785          | 0.6003   |
| 0.0756        | 21.0  | 777  | 1.6485          | 0.5850   |
| 0.0641        | 22.0  | 814  | 1.6257          | 0.6190   |
| 0.0387        | 23.0  | 851  | 1.6758          | 0.6105   |
| 0.0341        | 24.0  | 888  | 1.7239          | 0.6088   |
| 0.0227        | 25.0  | 925  | 1.7956          | 0.6020   |
| 0.0247        | 26.0  | 962  | 1.7542          | 0.6037   |
| 0.014         | 27.0  | 999  | 1.7693          | 0.6139   |
| 0.0152        | 28.0  | 1036 | 1.8133          | 0.5969   |
| 0.0125        | 29.0  | 1073 | 1.8082          | 0.6037   |
| 0.0116        | 30.0  | 1110 | 1.8129          | 0.5969   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3

label_0 label_1 label_2