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# vit-finetuned2

This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8828
- Accuracy: 0.746

## 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: 64
- eval_batch_size: 128
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 211  | 3.2058          | 0.2      |
| No log        | 2.0   | 422  | 2.7863          | 0.27     |
| 3.5109        | 3.0   | 633  | 2.6225          | 0.306    |
| 3.5109        | 4.0   | 844  | 2.3383          | 0.392    |
| 2.6956        | 5.0   | 1055 | 2.1045          | 0.456    |
| 2.6956        | 6.0   | 1266 | 1.8551          | 0.504    |
| 2.6956        | 7.0   | 1477 | 1.6949          | 0.54     |
| 2.213         | 8.0   | 1688 | 1.5866          | 0.576    |
| 2.213         | 9.0   | 1899 | 1.3373          | 0.646    |
| 1.8406        | 10.0  | 2110 | 1.2958          | 0.64     |
| 1.8406        | 11.0  | 2321 | 1.3066          | 0.652    |
| 1.5618        | 12.0  | 2532 | 1.1972          | 0.664    |
| 1.5618        | 13.0  | 2743 | 1.1654          | 0.67     |
| 1.5618        | 14.0  | 2954 | 1.0900          | 0.7      |
| 1.3308        | 15.0  | 3165 | 1.0244          | 0.704    |
| 1.3308        | 16.0  | 3376 | 1.0534          | 0.706    |
| 1.1426        | 17.0  | 3587 | 0.9758          | 0.732    |
| 1.1426        | 18.0  | 3798 | 0.9583          | 0.716    |
| 1.0085        | 19.0  | 4009 | 0.9191          | 0.732    |
| 1.0085        | 20.0  | 4220 | 0.8828          | 0.746    |


### Framework versions

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

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