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# vit-base-patch16-224-Trial006-YEL_STEM3

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: 0.0370
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7214        | 1.0   | 2    | 0.6865          | 0.625    |
| 0.6538        | 2.0   | 4    | 0.6506          | 0.6875   |
| 0.5973        | 3.0   | 6    | 0.5406          | 0.7708   |
| 0.5867        | 4.0   | 8    | 0.4452          | 0.8125   |
| 0.4882        | 5.0   | 10   | 0.3944          | 0.9167   |
| 0.3508        | 6.0   | 12   | 0.3255          | 0.8125   |
| 0.3367        | 7.0   | 14   | 0.2000          | 0.9375   |
| 0.2721        | 8.0   | 16   | 0.1377          | 0.9792   |
| 0.2401        | 9.0   | 18   | 0.0991          | 0.9792   |
| 0.242         | 10.0  | 20   | 0.0952          | 0.9583   |
| 0.2074        | 11.0  | 22   | 0.1278          | 0.9375   |
| 0.2048        | 12.0  | 24   | 0.0370          | 1.0      |
| 0.1933        | 13.0  | 26   | 0.1006          | 0.9375   |
| 0.1869        | 14.0  | 28   | 0.0348          | 1.0      |
| 0.2057        | 15.0  | 30   | 0.1574          | 0.9375   |
| 0.2368        | 16.0  | 32   | 0.0518          | 0.9792   |
| 0.1114        | 17.0  | 34   | 0.0149          | 1.0      |
| 0.1486        | 18.0  | 36   | 0.0187          | 1.0      |
| 0.1161        | 19.0  | 38   | 0.0083          | 1.0      |
| 0.1133        | 20.0  | 40   | 0.0062          | 1.0      |
| 0.1085        | 21.0  | 42   | 0.0108          | 1.0      |
| 0.1349        | 22.0  | 44   | 0.0148          | 1.0      |
| 0.1076        | 23.0  | 46   | 0.0080          | 1.0      |
| 0.1178        | 24.0  | 48   | 0.0137          | 1.0      |
| 0.1566        | 25.0  | 50   | 0.0074          | 1.0      |
| 0.1578        | 26.0  | 52   | 0.0064          | 1.0      |
| 0.1039        | 27.0  | 54   | 0.0077          | 1.0      |
| 0.1585        | 28.0  | 56   | 0.0058          | 1.0      |
| 0.1299        | 29.0  | 58   | 0.0130          | 1.0      |
| 0.1059        | 30.0  | 60   | 0.0075          | 1.0      |
| 0.1162        | 31.0  | 62   | 0.0151          | 1.0      |
| 0.1147        | 32.0  | 64   | 0.0100          | 1.0      |
| 0.1226        | 33.0  | 66   | 0.0581          | 0.9792   |
| 0.1264        | 34.0  | 68   | 0.1029          | 0.9792   |
| 0.0858        | 35.0  | 70   | 0.0594          | 0.9792   |
| 0.0671        | 36.0  | 72   | 0.0119          | 1.0      |
| 0.1381        | 37.0  | 74   | 0.0084          | 1.0      |
| 0.1054        | 38.0  | 76   | 0.0121          | 1.0      |
| 0.0969        | 39.0  | 78   | 0.0273          | 0.9792   |
| 0.1168        | 40.0  | 80   | 0.0203          | 0.9792   |
| 0.1065        | 41.0  | 82   | 0.0061          | 1.0      |
| 0.14          | 42.0  | 84   | 0.0041          | 1.0      |
| 0.1186        | 43.0  | 86   | 0.0088          | 1.0      |
| 0.0818        | 44.0  | 88   | 0.0214          | 0.9792   |
| 0.0676        | 45.0  | 90   | 0.0148          | 1.0      |
| 0.043         | 46.0  | 92   | 0.0105          | 1.0      |
| 0.0731        | 47.0  | 94   | 0.0085          | 1.0      |
| 0.1297        | 48.0  | 96   | 0.0082          | 1.0      |
| 0.1191        | 49.0  | 98   | 0.0086          | 1.0      |
| 0.0657        | 50.0  | 100  | 0.0090          | 1.0      |


### Framework versions

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

plant2 plant3