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# vit-base-patch16-224-Trial006-007-008-YEL_STEM1

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: 0.0457
- Accuracy: 0.9912

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7163        | 0.89  | 4    | 0.7036          | 0.5175   |
| 0.7183        | 2.0   | 9    | 0.6982          | 0.5439   |
| 0.6561        | 2.89  | 13   | 0.5914          | 0.6667   |
| 0.5799        | 4.0   | 18   | 0.6411          | 0.5526   |
| 0.5731        | 4.89  | 22   | 0.4833          | 0.8158   |
| 0.5162        | 6.0   | 27   | 0.4483          | 0.7807   |
| 0.4738        | 6.89  | 31   | 0.3961          | 0.8596   |
| 0.3283        | 8.0   | 36   | 0.2897          | 0.8772   |
| 0.3365        | 8.89  | 40   | 0.2774          | 0.8860   |
| 0.5987        | 10.0  | 45   | 0.2617          | 0.8947   |
| 0.3633        | 10.89 | 49   | 0.2661          | 0.8772   |
| 0.3342        | 12.0  | 54   | 0.2269          | 0.9211   |
| 0.3406        | 12.89 | 58   | 0.1903          | 0.9211   |
| 0.2331        | 14.0  | 63   | 0.2075          | 0.9123   |
| 0.2494        | 14.89 | 67   | 0.1345          | 0.9474   |
| 0.3143        | 16.0  | 72   | 0.1508          | 0.9298   |
| 0.2622        | 16.89 | 76   | 0.1267          | 0.9298   |
| 0.2894        | 18.0  | 81   | 0.0921          | 0.9737   |
| 0.2105        | 18.89 | 85   | 0.1058          | 0.9298   |
| 0.2011        | 20.0  | 90   | 0.1021          | 0.9561   |
| 0.1977        | 20.89 | 94   | 0.1122          | 0.9561   |
| 0.2685        | 22.0  | 99   | 0.1656          | 0.9298   |
| 0.2394        | 22.89 | 103  | 0.1197          | 0.9561   |
| 0.2394        | 24.0  | 108  | 0.1461          | 0.9211   |
| 0.1523        | 24.89 | 112  | 0.0969          | 0.9649   |
| 0.2231        | 26.0  | 117  | 0.0827          | 0.9649   |
| 0.1887        | 26.89 | 121  | 0.0979          | 0.9561   |
| 0.1656        | 28.0  | 126  | 0.0907          | 0.9386   |
| 0.1824        | 28.89 | 130  | 0.1009          | 0.9561   |
| 0.2443        | 30.0  | 135  | 0.1249          | 0.9474   |
| 0.2082        | 30.89 | 139  | 0.0755          | 0.9649   |
| 0.1276        | 32.0  | 144  | 0.0531          | 0.9825   |
| 0.1857        | 32.89 | 148  | 0.0707          | 0.9561   |
| 0.1676        | 34.0  | 153  | 0.0570          | 0.9825   |
| 0.1992        | 34.89 | 157  | 0.0591          | 0.9737   |
| 0.2283        | 36.0  | 162  | 0.0575          | 0.9737   |
| 0.2125        | 36.89 | 166  | 0.0519          | 0.9825   |
| 0.1915        | 38.0  | 171  | 0.0457          | 0.9912   |
| 0.1969        | 38.89 | 175  | 0.0644          | 0.9561   |
| 0.1522        | 40.0  | 180  | 0.0771          | 0.9561   |
| 0.1037        | 40.89 | 184  | 0.0557          | 0.9561   |
| 0.2348        | 42.0  | 189  | 0.0470          | 0.9737   |
| 0.1674        | 42.89 | 193  | 0.0469          | 0.9737   |
| 0.0874        | 44.0  | 198  | 0.0483          | 0.9737   |
| 0.1605        | 44.44 | 200  | 0.0485          | 0.9649   |


### Framework versions

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

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