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# v2_vit-base-patch16-224-in21k-finetuned-gecko

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1464
- Accuracy: 0.9572

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9727        | 1.0   | 76   | 2.7860          | 0.4906   |
| 1.8126        | 1.99  | 152  | 1.4636          | 0.6511   |
| 1.141         | 2.99  | 228  | 1.0104          | 0.7302   |
| 0.7464        | 4.0   | 305  | 0.8833          | 0.7382   |
| 0.6327        | 5.0   | 381  | 0.6328          | 0.8140   |
| 0.5424        | 5.99  | 457  | 0.6602          | 0.8103   |
| 0.4628        | 6.99  | 533  | 0.5417          | 0.8466   |
| 0.3852        | 8.0   | 610  | 0.5533          | 0.8405   |
| 0.3821        | 9.0   | 686  | 0.3930          | 0.8888   |
| 0.316         | 9.99  | 762  | 0.3375          | 0.9014   |
| 0.2907        | 10.99 | 838  | 0.3326          | 0.9088   |
| 0.2597        | 12.0  | 915  | 0.2484          | 0.9304   |
| 0.2387        | 13.0  | 991  | 0.2177          | 0.9359   |
| 0.221         | 13.99 | 1067 | 0.1708          | 0.9520   |
| 0.2017        | 14.95 | 1140 | 0.1464          | 0.9572   |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.13.3

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