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# 21BAI1229

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4078
- Accuracy: 0.8734

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.6034        | 0.9873  | 39   | 2.0544          | 0.4520   |
| 1.4429        | 2.0     | 79   | 0.7736          | 0.7849   |
| 0.8307        | 2.9873  | 118  | 0.5456          | 0.8413   |
| 0.6814        | 4.0     | 158  | 0.4881          | 0.8516   |
| 0.6199        | 4.9873  | 197  | 0.4614          | 0.8528   |
| 0.5578        | 6.0     | 237  | 0.4419          | 0.8615   |
| 0.5198        | 6.9873  | 276  | 0.4485          | 0.8603   |
| 0.4811        | 8.0     | 316  | 0.4355          | 0.8659   |
| 0.4568        | 8.9873  | 355  | 0.4182          | 0.8651   |
| 0.4268        | 10.0    | 395  | 0.4094          | 0.8702   |
| 0.4281        | 10.9873 | 434  | 0.4158          | 0.8706   |
| 0.4143        | 12.0    | 474  | 0.4078          | 0.8734   |
| 0.4009        | 12.9873 | 513  | 0.4066          | 0.8714   |
| 0.3642        | 14.0    | 553  | 0.4131          | 0.8683   |
| 0.3659        | 14.9873 | 592  | 0.4047          | 0.8726   |
| 0.3487        | 16.0    | 632  | 0.4054          | 0.8710   |
| 0.35          | 16.9873 | 671  | 0.4107          | 0.8722   |
| 0.3291        | 18.0    | 711  | 0.4099          | 0.8698   |
| 0.338         | 18.9873 | 750  | 0.4063          | 0.8718   |
| 0.3419        | 19.7468 | 780  | 0.4066          | 0.8702   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

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