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# vit-base-beans-demo-v5

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 ikram98ai/compliance_verification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5769
- Accuracy: 0.6585

## 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: 128
- eval_batch_size: 256
- 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5984        | 0.2459 | 30   | 0.5906          | 0.6400   |
| 0.6018        | 0.4918 | 60   | 0.5841          | 0.6579   |
| 0.5816        | 0.7377 | 90   | 0.5819          | 0.6433   |
| 0.594         | 0.9836 | 120  | 0.5769          | 0.6585   |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0

compliant non-compliant