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# vit-base-patch16-224-Trial007-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: 0.1948
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8588        | 0.89  | 2    | 0.7925          | 0.4815   |
| 0.7235        | 1.78  | 4    | 0.6471          | 0.6852   |
| 0.6009        | 2.67  | 6    | 0.5246          | 0.7222   |
| 0.4196        | 4.0   | 9    | 0.3422          | 0.9074   |
| 0.4022        | 4.89  | 11   | 0.3213          | 0.9259   |
| 0.3531        | 5.78  | 13   | 0.1948          | 1.0      |
| 0.3095        | 6.67  | 15   | 0.1196          | 1.0      |
| 0.283         | 8.0   | 18   | 0.0666          | 1.0      |
| 0.1607        | 8.89  | 20   | 0.0401          | 1.0      |
| 0.1459        | 9.78  | 22   | 0.0302          | 1.0      |
| 0.1325        | 10.67 | 24   | 0.0223          | 1.0      |
| 0.1362        | 12.0  | 27   | 0.0205          | 1.0      |
| 0.1623        | 12.89 | 29   | 0.0094          | 1.0      |
| 0.0974        | 13.78 | 31   | 0.0046          | 1.0      |
| 0.1077        | 14.67 | 33   | 0.0054          | 1.0      |
| 0.0742        | 16.0  | 36   | 0.0040          | 1.0      |
| 0.1468        | 16.89 | 38   | 0.0030          | 1.0      |
| 0.077         | 17.78 | 40   | 0.0041          | 1.0      |
| 0.0907        | 18.67 | 42   | 0.0109          | 1.0      |
| 0.0363        | 20.0  | 45   | 0.0023          | 1.0      |
| 0.0519        | 20.89 | 47   | 0.0016          | 1.0      |
| 0.0672        | 21.78 | 49   | 0.0015          | 1.0      |
| 0.0894        | 22.67 | 51   | 0.0020          | 1.0      |
| 0.0267        | 24.0  | 54   | 0.0020          | 1.0      |
| 0.0639        | 24.89 | 56   | 0.0019          | 1.0      |
| 0.0675        | 25.78 | 58   | 0.0023          | 1.0      |
| 0.0508        | 26.67 | 60   | 0.0020          | 1.0      |
| 0.0509        | 28.0  | 63   | 0.0014          | 1.0      |
| 0.0573        | 28.89 | 65   | 0.0018          | 1.0      |
| 0.0584        | 29.78 | 67   | 0.0014          | 1.0      |
| 0.0657        | 30.67 | 69   | 0.0012          | 1.0      |
| 0.0635        | 32.0  | 72   | 0.0009          | 1.0      |
| 0.0617        | 32.89 | 74   | 0.0008          | 1.0      |
| 0.0614        | 33.78 | 76   | 0.0008          | 1.0      |
| 0.0614        | 34.67 | 78   | 0.0009          | 1.0      |
| 0.0618        | 36.0  | 81   | 0.0008          | 1.0      |
| 0.0384        | 36.89 | 83   | 0.0008          | 1.0      |
| 0.0565        | 37.78 | 85   | 0.0008          | 1.0      |
| 0.0784        | 38.67 | 87   | 0.0008          | 1.0      |
| 0.0313        | 40.0  | 90   | 0.0007          | 1.0      |
| 0.0496        | 40.89 | 92   | 0.0007          | 1.0      |
| 0.0273        | 41.78 | 94   | 0.0008          | 1.0      |
| 0.0448        | 42.67 | 96   | 0.0008          | 1.0      |
| 0.0948        | 44.0  | 99   | 0.0007          | 1.0      |
| 0.0371        | 44.44 | 100  | 0.0007          | 1.0      |


### Framework versions

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

plant2 plant3