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# vit-ena24-MD

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the ena24_MD dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6827
- Accuracy: 0.6826

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4013        | 0.1259 | 100  | 1.8994          | 0.6631   |
| 0.4178        | 0.2519 | 200  | 2.0700          | 0.5938   |
| 0.336         | 0.3778 | 300  | 1.6827          | 0.6826   |
| 0.2547        | 0.5038 | 400  | 1.8338          | 0.6582   |
| 0.1166        | 0.6297 | 500  | 1.9549          | 0.6699   |
| 0.0555        | 0.7557 | 600  | 1.7759          | 0.7021   |
| 0.3521        | 0.8816 | 700  | 2.0155          | 0.6592   |
| 0.0144        | 1.0076 | 800  | 1.9693          | 0.6738   |
| 0.0847        | 1.1335 | 900  | 1.7930          | 0.7227   |
| 0.0041        | 1.2594 | 1000 | 1.7101          | 0.7334   |
| 0.0232        | 1.3854 | 1100 | 1.7127          | 0.7324   |
| 0.1154        | 1.5113 | 1200 | 1.8169          | 0.7236   |
| 0.0355        | 1.6373 | 1300 | 1.7981          | 0.7334   |
| 0.0042        | 1.7632 | 1400 | 1.7519          | 0.7451   |
| 0.0435        | 1.8892 | 1500 | 1.8185          | 0.7344   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1

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