---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distill-vit
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distill-vit

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4751
- Accuracy: 0.7656

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8986        | 1.0   | 65   | 0.7788          | 0.4286   |
| 0.8556        | 2.0   | 130  | 0.9774          | 0.4812   |
| 0.7581        | 3.0   | 195  | 0.6150          | 0.6541   |
| 0.6434        | 4.0   | 260  | 0.6455          | 0.6090   |
| 0.609         | 5.0   | 325  | 0.5329          | 0.7143   |
| 0.5503        | 6.0   | 390  | 0.5829          | 0.6466   |
| 0.5492        | 7.0   | 455  | 0.6716          | 0.6917   |
| 0.504         | 8.0   | 520  | 0.5342          | 0.6917   |
| 0.4966        | 9.0   | 585  | 0.5668          | 0.6617   |
| 0.4978        | 10.0  | 650  | 0.5347          | 0.6767   |
| 0.4535        | 11.0  | 715  | 0.5580          | 0.6090   |
| 0.4415        | 12.0  | 780  | 0.5085          | 0.7444   |
| 0.4308        | 13.0  | 845  | 0.5131          | 0.7068   |
| 0.4247        | 14.0  | 910  | 0.4808          | 0.7068   |
| 0.4307        | 15.0  | 975  | 0.5542          | 0.6917   |
| 0.4165        | 16.0  | 1040 | 0.5410          | 0.6992   |
| 0.3975        | 17.0  | 1105 | 0.5944          | 0.6015   |
| 0.3942        | 18.0  | 1170 | 0.4730          | 0.6917   |
| 0.3932        | 19.0  | 1235 | 0.4806          | 0.6917   |
| 0.3437        | 20.0  | 1300 | 0.5341          | 0.6842   |
| 0.3628        | 21.0  | 1365 | 0.5836          | 0.6692   |
| 0.3483        | 22.0  | 1430 | 0.6234          | 0.6316   |
| 0.3318        | 23.0  | 1495 | 0.4950          | 0.7143   |
| 0.3189        | 24.0  | 1560 | 0.4590          | 0.7068   |
| 0.3243        | 25.0  | 1625 | 0.5789          | 0.6692   |
| 0.3169        | 26.0  | 1690 | 0.5702          | 0.7218   |
| 0.3031        | 27.0  | 1755 | 0.4415          | 0.7519   |
| 0.2928        | 28.0  | 1820 | 0.4680          | 0.7368   |
| 0.3117        | 29.0  | 1885 | 0.5384          | 0.6842   |
| 0.3127        | 30.0  | 1950 | 0.5148          | 0.6767   |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.2.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1