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# vit-base-patch16-224-ethos-8

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: 0.3149
- Accuracy: 0.9

## 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: 8

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.8696 | 5    | 0.6399          | 0.7      |
| 0.7098        | 1.9130 | 11   | 0.4827          | 0.78     |
| 0.7098        | 2.9565 | 17   | 0.3961          | 0.85     |
| 0.245         | 4.0    | 23   | 0.4169          | 0.86     |
| 0.245         | 4.8696 | 28   | 0.3545          | 0.89     |
| 0.1238        | 5.9130 | 34   | 0.3214          | 0.91     |
| 0.051         | 6.9565 | 40   | 0.3149          | 0.9      |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1

rado rolex tissot