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# vit-base-patch16-224-Trial007-008-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: 0.0456
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7332        | 1.0   | 3    | 0.6494          | 0.6026   |
| 0.6264        | 2.0   | 6    | 0.5840          | 0.6667   |
| 0.5628        | 3.0   | 9    | 0.4136          | 0.8974   |
| 0.4492        | 4.0   | 12   | 0.3312          | 0.8846   |
| 0.3883        | 5.0   | 15   | 0.2472          | 0.9487   |
| 0.2958        | 6.0   | 18   | 0.2020          | 0.9359   |
| 0.2385        | 7.0   | 21   | 0.1272          | 0.9872   |
| 0.2359        | 8.0   | 24   | 0.1009          | 0.9872   |
| 0.2642        | 9.0   | 27   | 0.0896          | 0.9872   |
| 0.1856        | 10.0  | 30   | 0.0456          | 1.0      |
| 0.2115        | 11.0  | 33   | 0.0447          | 1.0      |
| 0.2067        | 12.0  | 36   | 0.0467          | 1.0      |
| 0.2059        | 13.0  | 39   | 0.0448          | 1.0      |
| 0.2108        | 14.0  | 42   | 0.0611          | 1.0      |
| 0.173         | 15.0  | 45   | 0.0410          | 1.0      |
| 0.2053        | 16.0  | 48   | 0.0445          | 1.0      |
| 0.1619        | 17.0  | 51   | 0.0521          | 1.0      |
| 0.2343        | 18.0  | 54   | 0.0318          | 1.0      |
| 0.2097        | 19.0  | 57   | 0.0438          | 1.0      |
| 0.1832        | 20.0  | 60   | 0.0538          | 1.0      |
| 0.1687        | 21.0  | 63   | 0.0375          | 1.0      |
| 0.145         | 22.0  | 66   | 0.0340          | 1.0      |
| 0.1398        | 23.0  | 69   | 0.0394          | 1.0      |
| 0.1898        | 24.0  | 72   | 0.0450          | 1.0      |
| 0.194         | 25.0  | 75   | 0.0515          | 1.0      |
| 0.1884        | 26.0  | 78   | 0.0494          | 1.0      |
| 0.1733        | 27.0  | 81   | 0.0374          | 1.0      |
| 0.1465        | 28.0  | 84   | 0.0385          | 1.0      |
| 0.156         | 29.0  | 87   | 0.0419          | 1.0      |
| 0.1929        | 30.0  | 90   | 0.0522          | 1.0      |
| 0.1189        | 31.0  | 93   | 0.0406          | 1.0      |
| 0.1605        | 32.0  | 96   | 0.0325          | 1.0      |
| 0.1543        | 33.0  | 99   | 0.0336          | 1.0      |
| 0.175         | 34.0  | 102  | 0.0456          | 1.0      |
| 0.1542        | 35.0  | 105  | 0.0547          | 1.0      |
| 0.1957        | 36.0  | 108  | 0.0529          | 1.0      |
| 0.1671        | 37.0  | 111  | 0.0453          | 1.0      |
| 0.1826        | 38.0  | 114  | 0.0388          | 1.0      |
| 0.1804        | 39.0  | 117  | 0.0391          | 1.0      |
| 0.1346        | 40.0  | 120  | 0.0390          | 1.0      |
| 0.1684        | 41.0  | 123  | 0.0400          | 1.0      |
| 0.143         | 42.0  | 126  | 0.0418          | 1.0      |
| 0.1588        | 43.0  | 129  | 0.0415          | 1.0      |
| 0.1403        | 44.0  | 132  | 0.0425          | 1.0      |
| 0.194         | 45.0  | 135  | 0.0422          | 1.0      |
| 0.1139        | 46.0  | 138  | 0.0421          | 1.0      |
| 0.1788        | 47.0  | 141  | 0.0419          | 1.0      |
| 0.1531        | 48.0  | 144  | 0.0416          | 1.0      |
| 0.187         | 49.0  | 147  | 0.0417          | 1.0      |
| 0.1564        | 50.0  | 150  | 0.0416          | 1.0      |


### Framework versions

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

plant2 plant3