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# vit-base-patch16-224-Trial006-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: 0.0494
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7481        | 0.89  | 2    | 0.6901          | 0.5455   |
| 0.6788        | 1.78  | 4    | 0.6743          | 0.6364   |
| 0.71          | 2.67  | 6    | 0.5935          | 0.6909   |
| 0.5911        | 4.0   | 9    | 0.5331          | 0.7091   |
| 0.572         | 4.89  | 11   | 0.4855          | 0.7636   |
| 0.5206        | 5.78  | 13   | 0.5816          | 0.7273   |
| 0.5029        | 6.67  | 15   | 0.4695          | 0.7818   |
| 0.4806        | 8.0   | 18   | 0.4680          | 0.8      |
| 0.3945        | 8.89  | 20   | 0.4059          | 0.8364   |
| 0.356         | 9.78  | 22   | 0.3764          | 0.8727   |
| 0.3153        | 10.67 | 24   | 0.3162          | 0.9091   |
| 0.3563        | 12.0  | 27   | 0.2654          | 0.8909   |
| 0.2904        | 12.89 | 29   | 0.2471          | 0.9091   |
| 0.2425        | 13.78 | 31   | 0.2265          | 0.8909   |
| 0.2402        | 14.67 | 33   | 0.2225          | 0.8909   |
| 0.2309        | 16.0  | 36   | 0.1752          | 0.9273   |
| 0.294         | 16.89 | 38   | 0.1769          | 0.9273   |
| 0.2004        | 17.78 | 40   | 0.1878          | 0.9091   |
| 0.2229        | 18.67 | 42   | 0.1126          | 0.9455   |
| 0.2804        | 20.0  | 45   | 0.1212          | 0.9273   |
| 0.2113        | 20.89 | 47   | 0.0494          | 1.0      |
| 0.1744        | 21.78 | 49   | 0.0767          | 0.9818   |
| 0.1645        | 22.67 | 51   | 0.0531          | 0.9818   |
| 0.2322        | 24.0  | 54   | 0.0757          | 0.9455   |
| 0.1934        | 24.89 | 56   | 0.0302          | 1.0      |
| 0.2172        | 25.78 | 58   | 0.1479          | 0.9455   |
| 0.1918        | 26.67 | 60   | 0.0374          | 0.9818   |
| 0.1948        | 28.0  | 63   | 0.1695          | 0.9273   |
| 0.2099        | 28.89 | 65   | 0.0743          | 0.9818   |
| 0.155         | 29.78 | 67   | 0.0275          | 1.0      |
| 0.1563        | 30.67 | 69   | 0.0273          | 1.0      |
| 0.149         | 32.0  | 72   | 0.0628          | 0.9818   |
| 0.1767        | 32.89 | 74   | 0.0388          | 0.9818   |
| 0.1828        | 33.78 | 76   | 0.0289          | 1.0      |
| 0.1825        | 34.67 | 78   | 0.0522          | 0.9636   |
| 0.197         | 36.0  | 81   | 0.0187          | 1.0      |
| 0.1534        | 36.89 | 83   | 0.0200          | 1.0      |
| 0.2099        | 37.78 | 85   | 0.0269          | 0.9818   |
| 0.1694        | 38.67 | 87   | 0.0176          | 1.0      |
| 0.101         | 40.0  | 90   | 0.0140          | 1.0      |
| 0.1488        | 40.89 | 92   | 0.0162          | 1.0      |
| 0.184         | 41.78 | 94   | 0.0175          | 1.0      |
| 0.182         | 42.67 | 96   | 0.0148          | 1.0      |
| 0.1364        | 44.0  | 99   | 0.0139          | 1.0      |
| 0.1332        | 44.44 | 100  | 0.0137          | 1.0      |


### Framework versions

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

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