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# Cinnamon-Plant-50-Epochs-Model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3989
- Accuracy: 0.8958
- F1: 0.8960

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.0428        | 1.0   | 18   | 0.2528          | 0.9167   | 0.9167 |
| 0.0218        | 2.0   | 36   | 0.3322          | 0.875    | 0.8763 |
| 0.0149        | 3.0   | 54   | 0.2954          | 0.875    | 0.8763 |
| 0.0121        | 4.0   | 72   | 0.2941          | 0.8958   | 0.8965 |
| 0.0106        | 5.0   | 90   | 0.3093          | 0.875    | 0.8763 |
| 0.0096        | 6.0   | 108  | 0.3130          | 0.8958   | 0.8965 |
| 0.0088        | 7.0   | 126  | 0.3227          | 0.875    | 0.8763 |
| 0.0082        | 8.0   | 144  | 0.3197          | 0.9167   | 0.9170 |
| 0.0077        | 9.0   | 162  | 0.3323          | 0.8958   | 0.8965 |
| 0.0073        | 10.0  | 180  | 0.3310          | 0.9167   | 0.9170 |
| 0.0069        | 11.0  | 198  | 0.3378          | 0.9167   | 0.9170 |
| 0.0066        | 12.0  | 216  | 0.3427          | 0.8958   | 0.8965 |
| 0.0064        | 13.0  | 234  | 0.3437          | 0.9167   | 0.9170 |
| 0.0061        | 14.0  | 252  | 0.3483          | 0.9167   | 0.9170 |
| 0.0059        | 15.0  | 270  | 0.3504          | 0.9167   | 0.9170 |
| 0.0057        | 16.0  | 288  | 0.3539          | 0.9167   | 0.9170 |
| 0.0055        | 17.0  | 306  | 0.3597          | 0.8958   | 0.8965 |
| 0.0054        | 18.0  | 324  | 0.3623          | 0.8958   | 0.8965 |
| 0.0052        | 19.0  | 342  | 0.3638          | 0.8958   | 0.8965 |
| 0.0051        | 20.0  | 360  | 0.3670          | 0.8958   | 0.8965 |
| 0.0049        | 21.0  | 378  | 0.3672          | 0.9167   | 0.9170 |
| 0.0048        | 22.0  | 396  | 0.3690          | 0.9167   | 0.9170 |
| 0.0047        | 23.0  | 414  | 0.3704          | 0.9167   | 0.9170 |
| 0.0046        | 24.0  | 432  | 0.3735          | 0.9167   | 0.9170 |
| 0.0045        | 25.0  | 450  | 0.3748          | 0.8958   | 0.8960 |
| 0.0044        | 26.0  | 468  | 0.3775          | 0.9167   | 0.9170 |
| 0.0044        | 27.0  | 486  | 0.3779          | 0.8958   | 0.8960 |
| 0.0043        | 28.0  | 504  | 0.3797          | 0.8958   | 0.8960 |
| 0.0042        | 29.0  | 522  | 0.3818          | 0.8958   | 0.8960 |
| 0.0041        | 30.0  | 540  | 0.3840          | 0.8958   | 0.8960 |
| 0.0041        | 31.0  | 558  | 0.3845          | 0.8958   | 0.8960 |
| 0.004         | 32.0  | 576  | 0.3861          | 0.8958   | 0.8960 |
| 0.004         | 33.0  | 594  | 0.3877          | 0.8958   | 0.8960 |
| 0.0039        | 34.0  | 612  | 0.3892          | 0.8958   | 0.8960 |
| 0.0039        | 35.0  | 630  | 0.3901          | 0.8958   | 0.8960 |
| 0.0038        | 36.0  | 648  | 0.3912          | 0.8958   | 0.8960 |
| 0.0038        | 37.0  | 666  | 0.3921          | 0.8958   | 0.8960 |
| 0.0038        | 38.0  | 684  | 0.3929          | 0.8958   | 0.8960 |
| 0.0037        | 39.0  | 702  | 0.3935          | 0.8958   | 0.8960 |
| 0.0037        | 40.0  | 720  | 0.3940          | 0.8958   | 0.8960 |
| 0.0037        | 41.0  | 738  | 0.3951          | 0.8958   | 0.8960 |
| 0.0036        | 42.0  | 756  | 0.3958          | 0.8958   | 0.8960 |
| 0.0036        | 43.0  | 774  | 0.3964          | 0.8958   | 0.8960 |
| 0.0036        | 44.0  | 792  | 0.3973          | 0.8958   | 0.8960 |
| 0.0036        | 45.0  | 810  | 0.3978          | 0.8958   | 0.8960 |
| 0.0036        | 46.0  | 828  | 0.3982          | 0.8958   | 0.8960 |
| 0.0036        | 47.0  | 846  | 0.3985          | 0.8958   | 0.8960 |
| 0.0036        | 48.0  | 864  | 0.3987          | 0.8958   | 0.8960 |
| 0.0035        | 49.0  | 882  | 0.3989          | 0.8958   | 0.8960 |
| 0.0035        | 50.0  | 900  | 0.3989          | 0.8958   | 0.8960 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

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