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# vit-base-patch16-224-ethosrealdata

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2117
- Accuracy: 0.9340

## 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: 0.0002
- 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.9707        | 0.9913 | 57   | 0.6825          | 0.8160   |
| 0.3507        | 2.0    | 115  | 0.3680          | 0.8909   |
| 0.2002        | 2.9913 | 172  | 0.3121          | 0.9023   |
| 0.1249        | 4.0    | 230  | 0.2951          | 0.9150   |
| 0.1002        | 4.9913 | 287  | 0.2596          | 0.9251   |
| 0.1014        | 6.0    | 345  | 0.2615          | 0.9251   |
| 0.1261        | 6.9913 | 402  | 0.2437          | 0.9365   |
| 0.0556        | 8.0    | 460  | 0.2198          | 0.9416   |
| 0.0415        | 8.9913 | 517  | 0.2119          | 0.9416   |
| 0.0294        | 9.9130 | 570  | 0.2117          | 0.9340   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

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