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# vit-base-patch16-224-Trial008-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: 0.1847
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5774        | 1.0   | 1    | 0.6707          | 0.5294   |
| 0.3598        | 2.0   | 3    | 0.5525          | 0.8235   |
| 0.1477        | 3.0   | 5    | 0.3968          | 0.9412   |
| 0.3936        | 4.0   | 6    | 0.4487          | 0.6471   |
| 0.3762        | 5.0   | 7    | 0.3782          | 0.7647   |
| 0.2275        | 6.0   | 9    | 0.1847          | 1.0      |
| 0.099         | 7.0   | 11   | 0.2053          | 0.9412   |
| 0.2703        | 8.0   | 12   | 0.1943          | 0.9412   |
| 0.2363        | 9.0   | 13   | 0.1228          | 0.9412   |
| 0.1336        | 10.0  | 15   | 0.0758          | 1.0      |
| 0.0772        | 11.0  | 17   | 0.0553          | 1.0      |
| 0.2227        | 12.0  | 18   | 0.0449          | 1.0      |
| 0.1975        | 13.0  | 19   | 0.0417          | 1.0      |
| 0.1401        | 14.0  | 21   | 0.0391          | 1.0      |
| 0.0541        | 15.0  | 23   | 0.0216          | 1.0      |
| 0.1465        | 16.0  | 24   | 0.0232          | 1.0      |
| 0.1583        | 17.0  | 25   | 0.0274          | 1.0      |
| 0.1226        | 18.0  | 27   | 0.0372          | 1.0      |
| 0.0826        | 19.0  | 29   | 0.0333          | 1.0      |
| 0.1634        | 20.0  | 30   | 0.0219          | 1.0      |
| 0.1904        | 21.0  | 31   | 0.0135          | 1.0      |
| 0.0755        | 22.0  | 33   | 0.0080          | 1.0      |
| 0.055         | 23.0  | 35   | 0.0071          | 1.0      |
| 0.1598        | 24.0  | 36   | 0.0072          | 1.0      |
| 0.1805        | 25.0  | 37   | 0.0068          | 1.0      |
| 0.1093        | 26.0  | 39   | 0.0062          | 1.0      |
| 0.0446        | 27.0  | 41   | 0.0061          | 1.0      |
| 0.1377        | 28.0  | 42   | 0.0062          | 1.0      |
| 0.1474        | 29.0  | 43   | 0.0063          | 1.0      |
| 0.0817        | 30.0  | 45   | 0.0066          | 1.0      |
| 0.0527        | 31.0  | 47   | 0.0067          | 1.0      |
| 0.1161        | 32.0  | 48   | 0.0067          | 1.0      |
| 0.1972        | 33.0  | 49   | 0.0067          | 1.0      |
| 0.0708        | 33.33 | 50   | 0.0067          | 1.0      |


### Framework versions

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

plant2 plant3