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# google-vit-Base-finetuned-food101

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5531
- Accuracy: 0.9727
- F1: 0.9740

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 3.4867        | 1.0    | 157  | 3.2502          | 0.8793   | 0.8778 |
| 2.0982        | 2.0    | 314  | 1.9278          | 0.9353   | 0.9355 |
| 1.5644        | 3.0    | 471  | 1.3466          | 0.9633   | 0.9639 |
| 1.1841        | 4.0    | 628  | 1.0414          | 0.9653   | 0.9662 |
| 1.0235        | 5.0    | 785  | 0.8482          | 0.9687   | 0.9696 |
| 0.8153        | 6.0    | 942  | 0.7218          | 0.9673   | 0.9688 |
| 0.7418        | 7.0    | 1099 | 0.6439          | 0.9687   | 0.9700 |
| 0.6897        | 8.0    | 1256 | 0.5831          | 0.972    | 0.9730 |
| 0.6453        | 9.0    | 1413 | 0.5531          | 0.9727   | 0.9740 |
| 0.6199        | 9.9408 | 1560 | 0.5457          | 0.9707   | 0.9720 |


### Framework versions

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

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