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# vit-base-patch16-224-Trial007-YEL_STEM3

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: 0.0840
- Accuracy: 1.0

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7133        | 0.89  | 2    | 0.6860          | 0.5926   |
| 0.6666        | 1.78  | 4    | 0.6151          | 0.7037   |
| 0.524         | 2.67  | 6    | 0.4915          | 0.8704   |
| 0.3759        | 4.0   | 9    | 0.3304          | 0.9074   |
| 0.3218        | 4.89  | 11   | 0.2177          | 0.9259   |
| 0.2764        | 5.78  | 13   | 0.1735          | 0.9630   |
| 0.2558        | 6.67  | 15   | 0.0840          | 1.0      |
| 0.7446        | 8.0   | 18   | 0.1256          | 0.9815   |
| 0.1251        | 8.89  | 20   | 0.0527          | 1.0      |
| 0.1491        | 9.78  | 22   | 0.0366          | 1.0      |
| 0.1559        | 10.67 | 24   | 0.0225          | 1.0      |
| 0.0916        | 12.0  | 27   | 0.0139          | 1.0      |
| 0.0751        | 12.89 | 29   | 0.0112          | 1.0      |
| 0.084         | 13.78 | 31   | 0.0102          | 1.0      |
| 0.0741        | 14.67 | 33   | 0.0103          | 1.0      |
| 0.065         | 16.0  | 36   | 0.0071          | 1.0      |
| 0.1019        | 16.89 | 38   | 0.0061          | 1.0      |
| 0.061         | 17.78 | 40   | 0.0052          | 1.0      |
| 0.0751        | 18.67 | 42   | 0.0045          | 1.0      |
| 0.0336        | 20.0  | 45   | 0.0064          | 1.0      |
| 0.0362        | 20.89 | 47   | 0.0038          | 1.0      |
| 0.073         | 21.78 | 49   | 0.0037          | 1.0      |
| 0.0748        | 22.67 | 51   | 0.0050          | 1.0      |
| 0.0543        | 24.0  | 54   | 0.0056          | 1.0      |
| 0.0408        | 24.89 | 56   | 0.0048          | 1.0      |
| 0.0729        | 25.78 | 58   | 0.0050          | 1.0      |
| 0.0638        | 26.67 | 60   | 0.0035          | 1.0      |
| 0.042         | 28.0  | 63   | 0.0029          | 1.0      |
| 0.0982        | 28.89 | 65   | 0.0025          | 1.0      |
| 0.0238        | 29.78 | 67   | 0.0023          | 1.0      |
| 0.0536        | 30.67 | 69   | 0.0032          | 1.0      |
| 0.1131        | 32.0  | 72   | 0.0029          | 1.0      |
| 0.0569        | 32.89 | 74   | 0.0030          | 1.0      |
| 0.0717        | 33.78 | 76   | 0.0034          | 1.0      |
| 0.0567        | 34.67 | 78   | 0.0037          | 1.0      |
| 0.0807        | 36.0  | 81   | 0.0039          | 1.0      |
| 0.0888        | 36.89 | 83   | 0.0039          | 1.0      |
| 0.0548        | 37.78 | 85   | 0.0039          | 1.0      |
| 0.078         | 38.67 | 87   | 0.0040          | 1.0      |
| 0.0453        | 40.0  | 90   | 0.0041          | 1.0      |
| 0.0442        | 40.89 | 92   | 0.0042          | 1.0      |
| 0.0425        | 41.78 | 94   | 0.0041          | 1.0      |
| 0.0619        | 42.67 | 96   | 0.0041          | 1.0      |
| 0.0437        | 44.0  | 99   | 0.0040          | 1.0      |
| 0.0552        | 44.44 | 100  | 0.0040          | 1.0      |


### Framework versions

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

plant2 plant3