
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-base-patch16-224-Trial007-008-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: 0.1014
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7829        | 1.0   | 3    | 0.6908          | 0.5769   |
| 0.609         | 2.0   | 6    | 0.6573          | 0.6795   |
| 0.5343        | 3.0   | 9    | 0.4127          | 0.8205   |
| 0.4062        | 4.0   | 12   | 0.3091          | 0.8974   |
| 0.322         | 5.0   | 15   | 0.1731          | 0.9744   |
| 0.2056        | 6.0   | 18   | 0.1610          | 0.9615   |
| 0.265         | 7.0   | 21   | 0.1083          | 0.9744   |
| 0.2145        | 8.0   | 24   | 0.0809          | 0.9872   |
| 0.2869        | 9.0   | 27   | 0.1014          | 1.0      |
| 0.1803        | 10.0  | 30   | 0.0499          | 1.0      |
| 0.2353        | 11.0  | 33   | 0.0597          | 1.0      |
| 0.1768        | 12.0  | 36   | 0.0614          | 1.0      |
| 0.2124        | 13.0  | 39   | 0.0574          | 1.0      |
| 0.2366        | 14.0  | 42   | 0.0844          | 1.0      |
| 0.2283        | 15.0  | 45   | 0.0603          | 0.9872   |
| 0.246         | 16.0  | 48   | 0.0537          | 1.0      |
| 0.1636        | 17.0  | 51   | 0.0569          | 1.0      |
| 0.1983        | 18.0  | 54   | 0.0565          | 1.0      |
| 0.1817        | 19.0  | 57   | 0.0684          | 1.0      |
| 0.1835        | 20.0  | 60   | 0.0580          | 1.0      |
| 0.1293        | 21.0  | 63   | 0.0324          | 1.0      |
| 0.1985        | 22.0  | 66   | 0.0398          | 1.0      |
| 0.1827        | 23.0  | 69   | 0.0596          | 1.0      |
| 0.2516        | 24.0  | 72   | 0.0545          | 1.0      |
| 0.1871        | 25.0  | 75   | 0.0620          | 1.0      |
| 0.1853        | 26.0  | 78   | 0.0558          | 1.0      |
| 0.2257        | 27.0  | 81   | 0.0488          | 1.0      |
| 0.159         | 28.0  | 84   | 0.0500          | 1.0      |
| 0.1767        | 29.0  | 87   | 0.0508          | 1.0      |
| 0.1841        | 30.0  | 90   | 0.0599          | 1.0      |
| 0.1234        | 31.0  | 93   | 0.0602          | 1.0      |
| 0.1836        | 32.0  | 96   | 0.0504          | 1.0      |
| 0.1898        | 33.0  | 99   | 0.0477          | 1.0      |
| 0.187         | 34.0  | 102  | 0.0560          | 1.0      |
| 0.1405        | 35.0  | 105  | 0.0672          | 1.0      |
| 0.188         | 36.0  | 108  | 0.0783          | 1.0      |
| 0.1855        | 37.0  | 111  | 0.0727          | 1.0      |
| 0.1833        | 38.0  | 114  | 0.0611          | 1.0      |
| 0.1957        | 39.0  | 117  | 0.0552          | 1.0      |
| 0.1463        | 40.0  | 120  | 0.0529          | 1.0      |
| 0.1255        | 41.0  | 123  | 0.0541          | 1.0      |
| 0.1558        | 42.0  | 126  | 0.0526          | 1.0      |
| 0.148         | 43.0  | 129  | 0.0513          | 1.0      |
| 0.1703        | 44.0  | 132  | 0.0615          | 1.0      |
| 0.1951        | 45.0  | 135  | 0.0547          | 1.0      |
| 0.1637        | 46.0  | 138  | 0.0536          | 1.0      |
| 0.1754        | 47.0  | 141  | 0.0506          | 1.0      |
| 0.1444        | 48.0  | 144  | 0.0519          | 1.0      |
| 0.1726        | 49.0  | 147  | 0.0545          | 1.0      |
| 0.1439        | 50.0  | 150  | 0.0553          | 1.0      |


### Framework versions

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

plant2 plant3