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# 0.50-Train-Test-vit-large

This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8804
- Accuracy: 0.8098

## 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: 25

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.3722        | 0.9825  | 14   | 1.8140          | 0.3758   |
| 1.7117        | 1.9649  | 28   | 0.9446          | 0.7383   |
| 0.3741        | 2.9474  | 42   | 0.8083          | 0.7338   |
| 0.1709        | 4.0     | 57   | 0.7460          | 0.7562   |
| 0.0166        | 4.9825  | 71   | 0.7632          | 0.7763   |
| 0.0087        | 5.9649  | 85   | 0.9165          | 0.7629   |
| 0.013         | 6.9474  | 99   | 0.8161          | 0.7942   |
| 0.0029        | 8.0     | 114  | 0.8216          | 0.7964   |
| 0.0016        | 8.9825  | 128  | 0.8461          | 0.7919   |
| 0.0009        | 9.9649  | 142  | 0.8528          | 0.7919   |
| 0.0007        | 10.9474 | 156  | 0.8539          | 0.8031   |
| 0.0006        | 12.0    | 171  | 0.8586          | 0.8054   |
| 0.0006        | 12.9825 | 185  | 0.8622          | 0.8076   |
| 0.0005        | 13.9649 | 199  | 0.8649          | 0.8098   |
| 0.0005        | 14.9474 | 213  | 0.8677          | 0.8098   |
| 0.0005        | 16.0    | 228  | 0.8706          | 0.8098   |
| 0.0004        | 16.9825 | 242  | 0.8729          | 0.8098   |
| 0.0004        | 17.9649 | 256  | 0.8747          | 0.8098   |
| 0.0004        | 18.9474 | 270  | 0.8764          | 0.8076   |
| 0.0004        | 20.0    | 285  | 0.8776          | 0.8098   |
| 0.0004        | 20.9825 | 299  | 0.8789          | 0.8076   |
| 0.0003        | 21.9649 | 313  | 0.8794          | 0.8098   |
| 0.0003        | 22.9474 | 327  | 0.8801          | 0.8098   |
| 0.0003        | 24.0    | 342  | 0.8804          | 0.8098   |
| 0.0003        | 24.5614 | 350  | 0.8804          | 0.8098   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1

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