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# vit-base-patch16-224-Trial006-YEL_STEM4

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: 0.0984
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7587        | 0.57  | 1    | 0.6296          | 0.7111   |
| 0.6884        | 1.71  | 3    | 0.7730          | 0.4      |
| 0.6112        | 2.86  | 5    | 0.5194          | 0.8222   |
| 0.5566        | 4.0   | 7    | 0.6194          | 0.6444   |
| 0.5216        | 4.57  | 8    | 0.5428          | 0.6889   |
| 0.4488        | 5.71  | 10   | 0.3884          | 0.8222   |
| 0.4438        | 6.86  | 12   | 0.3301          | 0.8444   |
| 0.3897        | 8.0   | 14   | 0.2362          | 0.9111   |
| 0.3789        | 8.57  | 15   | 0.1942          | 0.9333   |
| 0.3484        | 9.71  | 17   | 0.3995          | 0.8222   |
| 0.2727        | 10.86 | 19   | 0.1636          | 0.9556   |
| 0.209         | 12.0  | 21   | 0.1489          | 0.9556   |
| 0.2253        | 12.57 | 22   | 0.1712          | 0.9111   |
| 0.2407        | 13.71 | 24   | 0.2239          | 0.9111   |
| 0.1615        | 14.86 | 26   | 0.0984          | 1.0      |
| 0.1735        | 16.0  | 28   | 0.1231          | 0.9111   |
| 0.179         | 16.57 | 29   | 0.1203          | 0.9111   |
| 0.1464        | 17.71 | 31   | 0.0422          | 1.0      |
| 0.1444        | 18.86 | 33   | 0.0409          | 1.0      |
| 0.1758        | 20.0  | 35   | 0.0394          | 1.0      |
| 0.199         | 20.57 | 36   | 0.0246          | 1.0      |
| 0.1525        | 21.71 | 38   | 0.0179          | 1.0      |
| 0.1536        | 22.86 | 40   | 0.0441          | 1.0      |
| 0.115         | 24.0  | 42   | 0.0836          | 0.9333   |
| 0.106         | 24.57 | 43   | 0.0654          | 0.9778   |
| 0.1267        | 25.71 | 45   | 0.0285          | 1.0      |
| 0.1264        | 26.86 | 47   | 0.0199          | 1.0      |
| 0.1554        | 28.0  | 49   | 0.0192          | 1.0      |
| 0.1456        | 28.57 | 50   | 0.0195          | 1.0      |


### Framework versions

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

plant2 plant3