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# vit-base-patch16-224-Trial006-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: 0.0644
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7114        | 1.0   | 2    | 0.6552          | 0.5962   |
| 0.6552        | 2.0   | 4    | 0.6270          | 0.6346   |
| 0.5889        | 3.0   | 6    | 0.5689          | 0.75     |
| 0.5458        | 4.0   | 8    | 0.5344          | 0.75     |
| 0.4979        | 5.0   | 10   | 0.4562          | 0.8462   |
| 0.4068        | 6.0   | 12   | 0.4825          | 0.7308   |
| 0.3409        | 7.0   | 14   | 0.3131          | 0.8846   |
| 0.3453        | 8.0   | 16   | 0.2443          | 0.9231   |
| 0.2641        | 9.0   | 18   | 0.2463          | 0.8654   |
| 0.2402        | 10.0  | 20   | 0.1693          | 0.9231   |
| 0.2718        | 11.0  | 22   | 0.2417          | 0.9038   |
| 0.2348        | 12.0  | 24   | 0.1242          | 0.9423   |
| 0.1613        | 13.0  | 26   | 0.1589          | 0.9231   |
| 0.1651        | 14.0  | 28   | 0.0644          | 1.0      |
| 0.1885        | 15.0  | 30   | 0.0554          | 1.0      |
| 0.1593        | 16.0  | 32   | 0.1013          | 0.9615   |
| 0.1424        | 17.0  | 34   | 0.2931          | 0.8846   |
| 0.1535        | 18.0  | 36   | 0.1800          | 0.9038   |
| 0.1699        | 19.0  | 38   | 0.1044          | 0.9423   |
| 0.1899        | 20.0  | 40   | 0.0576          | 0.9808   |
| 0.1469        | 21.0  | 42   | 0.1152          | 0.9615   |
| 0.1512        | 22.0  | 44   | 0.1046          | 0.9615   |
| 0.1215        | 23.0  | 46   | 0.1317          | 0.9231   |
| 0.1071        | 24.0  | 48   | 0.0721          | 0.9615   |
| 0.154         | 25.0  | 50   | 0.0647          | 0.9615   |
| 0.1505        | 26.0  | 52   | 0.1563          | 0.9615   |
| 0.1422        | 27.0  | 54   | 0.0764          | 0.9615   |
| 0.109         | 28.0  | 56   | 0.1009          | 0.9808   |
| 0.2124        | 29.0  | 58   | 0.0943          | 0.9615   |
| 0.1342        | 30.0  | 60   | 0.0885          | 0.9615   |
| 0.1063        | 31.0  | 62   | 0.1581          | 0.9615   |
| 0.104         | 32.0  | 64   | 0.0704          | 0.9615   |
| 0.1256        | 33.0  | 66   | 0.0539          | 0.9808   |
| 0.1365        | 34.0  | 68   | 0.0844          | 0.9615   |
| 0.1141        | 35.0  | 70   | 0.1329          | 0.9615   |
| 0.1326        | 36.0  | 72   | 0.0829          | 0.9615   |
| 0.1106        | 37.0  | 74   | 0.0655          | 0.9615   |
| 0.1178        | 38.0  | 76   | 0.0676          | 0.9615   |
| 0.1031        | 39.0  | 78   | 0.0653          | 0.9615   |
| 0.0991        | 40.0  | 80   | 0.0633          | 0.9615   |
| 0.0924        | 41.0  | 82   | 0.0416          | 0.9808   |
| 0.1009        | 42.0  | 84   | 0.0360          | 0.9808   |
| 0.0834        | 43.0  | 86   | 0.0334          | 0.9808   |
| 0.1132        | 44.0  | 88   | 0.0578          | 0.9615   |
| 0.1428        | 45.0  | 90   | 0.1010          | 0.9615   |
| 0.0962        | 46.0  | 92   | 0.1100          | 0.9615   |
| 0.0917        | 47.0  | 94   | 0.1021          | 0.9615   |
| 0.1292        | 48.0  | 96   | 0.0808          | 0.9615   |
| 0.1036        | 49.0  | 98   | 0.0625          | 0.9615   |
| 0.0986        | 50.0  | 100  | 0.0535          | 0.9615   |


### Framework versions

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

plant2 plant3