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# flipped_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: 2.5433
- Accuracy: 0.4099

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3063        | 1.0   | 37   | 1.2485          | 0.4592   |
| 1.2272        | 2.0   | 74   | 1.1915          | 0.4626   |
| 1.1518        | 3.0   | 111  | 1.1770          | 0.4575   |
| 1.0504        | 4.0   | 148  | 1.1724          | 0.4745   |
| 0.9525        | 5.0   | 185  | 1.1966          | 0.4898   |
| 0.7485        | 6.0   | 222  | 1.2403          | 0.4626   |
| 0.5645        | 7.0   | 259  | 1.3973          | 0.4235   |
| 0.4645        | 8.0   | 296  | 1.4260          | 0.4898   |
| 0.374         | 9.0   | 333  | 1.5838          | 0.4405   |
| 0.2721        | 10.0  | 370  | 1.6747          | 0.4354   |
| 0.2679        | 11.0  | 407  | 1.7427          | 0.4507   |
| 0.2284        | 12.0  | 444  | 1.8097          | 0.4269   |
| 0.2003        | 13.0  | 481  | 1.9738          | 0.3997   |
| 0.1844        | 14.0  | 518  | 1.9745          | 0.4524   |
| 0.1631        | 15.0  | 555  | 2.0326          | 0.4456   |
| 0.1135        | 16.0  | 592  | 2.1294          | 0.4184   |
| 0.1188        | 17.0  | 629  | 2.1613          | 0.4065   |
| 0.1204        | 18.0  | 666  | 2.1795          | 0.4252   |
| 0.1083        | 19.0  | 703  | 2.2433          | 0.4167   |
| 0.0794        | 20.0  | 740  | 2.2762          | 0.4150   |
| 0.0589        | 21.0  | 777  | 2.3736          | 0.4065   |
| 0.0646        | 22.0  | 814  | 2.3644          | 0.4252   |
| 0.0744        | 23.0  | 851  | 2.4478          | 0.4099   |
| 0.0728        | 24.0  | 888  | 2.4367          | 0.4099   |
| 0.0382        | 25.0  | 925  | 2.5123          | 0.3997   |
| 0.033         | 26.0  | 962  | 2.5202          | 0.4031   |
| 0.0326        | 27.0  | 999  | 2.5145          | 0.4099   |
| 0.023         | 28.0  | 1036 | 2.5309          | 0.4099   |
| 0.0377        | 29.0  | 1073 | 2.5409          | 0.4099   |
| 0.0243        | 30.0  | 1110 | 2.5433          | 0.4099   |


### 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 label_3