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# beit-ena24

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the ena24 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9751
- Accuracy: 0.6809

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.8853        | 0.1302 | 100  | 2.8477          | 0.2176   |
| 2.7962        | 0.2604 | 200  | 2.5644          | 0.1985   |
| 2.4273        | 0.3906 | 300  | 2.3036          | 0.2885   |
| 2.1587        | 0.5208 | 400  | 2.1759          | 0.3305   |
| 2.1721        | 0.6510 | 500  | 2.0160          | 0.3405   |
| 2.0539        | 0.7812 | 600  | 1.8444          | 0.4084   |
| 1.7687        | 0.9115 | 700  | 1.7824          | 0.4069   |
| 1.7545        | 1.0417 | 800  | 1.6203          | 0.5092   |
| 1.5865        | 1.1719 | 900  | 1.5315          | 0.5176   |
| 1.3489        | 1.3021 | 1000 | 1.6056          | 0.5084   |
| 1.2064        | 1.4323 | 1100 | 1.2743          | 0.5878   |
| 1.1963        | 1.5625 | 1200 | 1.1703          | 0.6336   |
| 1.0333        | 1.6927 | 1300 | 1.1410          | 0.6412   |
| 1.1828        | 1.8229 | 1400 | 1.0684          | 0.6473   |
| 0.6996        | 1.9531 | 1500 | 0.9751          | 0.6809   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1

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