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# vit-base-patch16-224-Trial007-YEL_STEM2

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: 0.1172
- Accuracy: 0.9815

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6676        | 0.89  | 2    | 0.6180          | 0.7222   |
| 0.5805        | 1.78  | 4    | 0.5004          | 0.7593   |
| 0.5012        | 2.67  | 6    | 0.3783          | 0.9630   |
| 0.2794        | 4.0   | 9    | 0.2285          | 0.9630   |
| 0.2695        | 4.89  | 11   | 0.2551          | 0.8889   |
| 0.2782        | 5.78  | 13   | 0.1079          | 0.9630   |
| 0.2131        | 6.67  | 15   | 0.1205          | 0.9630   |
| 0.1537        | 8.0   | 18   | 0.1861          | 0.9630   |
| 0.1739        | 8.89  | 20   | 0.1172          | 0.9815   |
| 0.1059        | 9.78  | 22   | 0.1092          | 0.9815   |
| 0.146         | 10.67 | 24   | 0.1072          | 0.9815   |
| 0.088         | 12.0  | 27   | 0.1015          | 0.9815   |
| 0.1304        | 12.89 | 29   | 0.1151          | 0.9815   |
| 0.0924        | 13.78 | 31   | 0.1313          | 0.9815   |
| 0.091         | 14.67 | 33   | 0.1178          | 0.9815   |
| 0.0508        | 16.0  | 36   | 0.0971          | 0.9815   |
| 0.1004        | 16.89 | 38   | 0.1175          | 0.9815   |
| 0.1097        | 17.78 | 40   | 0.1423          | 0.9630   |
| 0.0758        | 18.67 | 42   | 0.1597          | 0.9630   |
| 0.0687        | 20.0  | 45   | 0.1205          | 0.9815   |
| 0.0513        | 20.89 | 47   | 0.1107          | 0.9815   |
| 0.0755        | 21.78 | 49   | 0.1150          | 0.9815   |
| 0.0897        | 22.67 | 51   | 0.1332          | 0.9630   |
| 0.0439        | 24.0  | 54   | 0.1263          | 0.9815   |
| 0.0607        | 24.89 | 56   | 0.1111          | 0.9815   |
| 0.0719        | 25.78 | 58   | 0.1004          | 0.9815   |
| 0.0599        | 26.67 | 60   | 0.1064          | 0.9815   |
| 0.0613        | 28.0  | 63   | 0.1355          | 0.9815   |
| 0.0689        | 28.89 | 65   | 0.1444          | 0.9815   |
| 0.0754        | 29.78 | 67   | 0.1398          | 0.9815   |
| 0.0835        | 30.67 | 69   | 0.1345          | 0.9815   |
| 0.0801        | 32.0  | 72   | 0.1348          | 0.9815   |
| 0.0701        | 32.89 | 74   | 0.1365          | 0.9815   |
| 0.0647        | 33.78 | 76   | 0.1348          | 0.9815   |
| 0.0982        | 34.67 | 78   | 0.1346          | 0.9815   |
| 0.0671        | 36.0  | 81   | 0.1378          | 0.9815   |
| 0.054         | 36.89 | 83   | 0.1371          | 0.9815   |
| 0.0735        | 37.78 | 85   | 0.1355          | 0.9815   |
| 0.0736        | 38.67 | 87   | 0.1349          | 0.9815   |
| 0.0287        | 40.0  | 90   | 0.1329          | 0.9815   |
| 0.0539        | 40.89 | 92   | 0.1322          | 0.9815   |
| 0.0483        | 41.78 | 94   | 0.1324          | 0.9815   |
| 0.083         | 42.67 | 96   | 0.1319          | 0.9815   |
| 0.0558        | 44.0  | 99   | 0.1319          | 0.9815   |
| 0.0752        | 44.44 | 100  | 0.1319          | 0.9815   |


### Framework versions

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

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