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# vit-base-patch16-224-Trial006-007-008-YEL_STEM

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1837
- Accuracy: 0.9492

## 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: 60
- eval_batch_size: 60
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 240
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7399        | 0.89  | 4    | 0.7281          | 0.5085   |
| 0.6861        | 2.0   | 9    | 0.6326          | 0.6186   |
| 0.6362        | 2.89  | 13   | 0.6392          | 0.6610   |
| 0.5728        | 4.0   | 18   | 0.5497          | 0.6695   |
| 0.515         | 4.89  | 22   | 0.4464          | 0.8136   |
| 0.5437        | 6.0   | 27   | 0.4090          | 0.8136   |
| 0.4647        | 6.89  | 31   | 0.3873          | 0.8220   |
| 0.4616        | 8.0   | 36   | 0.4446          | 0.7712   |
| 0.4396        | 8.89  | 40   | 0.4029          | 0.8220   |
| 0.4354        | 10.0  | 45   | 0.3104          | 0.8559   |
| 0.4187        | 10.89 | 49   | 0.4200          | 0.8220   |
| 0.4639        | 12.0  | 54   | 0.2883          | 0.8898   |
| 0.3663        | 12.89 | 58   | 0.2667          | 0.9153   |
| 0.3169        | 14.0  | 63   | 0.3731          | 0.8644   |
| 0.4725        | 14.89 | 67   | 0.2759          | 0.8729   |
| 0.4438        | 16.0  | 72   | 0.3782          | 0.8559   |
| 0.361         | 16.89 | 76   | 0.2790          | 0.8983   |
| 0.3321        | 18.0  | 81   | 0.2890          | 0.8983   |
| 0.3071        | 18.89 | 85   | 0.2499          | 0.8814   |
| 0.333         | 20.0  | 90   | 0.2271          | 0.9068   |
| 0.2706        | 20.89 | 94   | 0.2631          | 0.8814   |
| 0.2963        | 22.0  | 99   | 0.2449          | 0.9068   |
| 0.323         | 22.89 | 103  | 0.1904          | 0.9322   |
| 0.2677        | 24.0  | 108  | 0.2341          | 0.9237   |
| 0.2473        | 24.89 | 112  | 0.2191          | 0.9237   |
| 0.2598        | 26.0  | 117  | 0.2106          | 0.9322   |
| 0.2733        | 26.89 | 121  | 0.1837          | 0.9492   |
| 0.2506        | 28.0  | 126  | 0.1828          | 0.9407   |
| 0.2315        | 28.89 | 130  | 0.2110          | 0.9153   |
| 0.2519        | 30.0  | 135  | 0.2288          | 0.9153   |
| 0.289         | 30.89 | 139  | 0.1781          | 0.9322   |
| 0.3309        | 32.0  | 144  | 0.1571          | 0.9322   |
| 0.2435        | 32.89 | 148  | 0.1778          | 0.9322   |
| 0.2643        | 34.0  | 153  | 0.2275          | 0.9153   |
| 0.2238        | 34.89 | 157  | 0.1777          | 0.9322   |
| 0.2773        | 36.0  | 162  | 0.1955          | 0.9322   |
| 0.2422        | 36.89 | 166  | 0.2019          | 0.9237   |
| 0.2812        | 38.0  | 171  | 0.1794          | 0.9492   |
| 0.2626        | 38.89 | 175  | 0.1884          | 0.9407   |
| 0.2059        | 40.0  | 180  | 0.1843          | 0.9322   |
| 0.2585        | 40.89 | 184  | 0.1721          | 0.9492   |
| 0.2022        | 42.0  | 189  | 0.1640          | 0.9492   |
| 0.2403        | 42.89 | 193  | 0.1660          | 0.9407   |
| 0.2771        | 44.0  | 198  | 0.1686          | 0.9407   |
| 0.2153        | 44.44 | 200  | 0.1684          | 0.9407   |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 1.12.1
- Datasets 2.12.0
- Tokenizers 0.13.1

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