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# vit-base-patch16-224-Trial006-007-008-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: 0.0188
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7014        | 0.94  | 4    | 0.6789          | 0.5872   |
| 0.6242        | 1.88  | 8    | 0.6182          | 0.6147   |
| 0.5903        | 2.82  | 12   | 0.5147          | 0.8165   |
| 0.516         | 4.0   | 17   | 0.4137          | 0.8440   |
| 0.4612        | 4.94  | 21   | 0.3127          | 0.8899   |
| 0.3615        | 5.88  | 25   | 0.2448          | 0.8899   |
| 0.2899        | 6.82  | 29   | 0.2502          | 0.9083   |
| 0.3271        | 8.0   | 34   | 0.2268          | 0.8899   |
| 0.3765        | 8.94  | 38   | 0.1419          | 0.9266   |
| 0.2954        | 9.88  | 42   | 0.1233          | 0.9450   |
| 0.2187        | 10.82 | 46   | 0.1541          | 0.9358   |
| 0.3391        | 12.0  | 51   | 0.1575          | 0.9266   |
| 0.2027        | 12.94 | 55   | 0.0838          | 0.9908   |
| 0.2894        | 13.88 | 59   | 0.0852          | 0.9633   |
| 0.1972        | 14.82 | 63   | 0.0648          | 0.9908   |
| 0.1533        | 16.0  | 68   | 0.0884          | 0.9908   |
| 0.1588        | 16.94 | 72   | 0.0951          | 0.9633   |
| 0.1746        | 17.88 | 76   | 0.0793          | 0.9725   |
| 0.2386        | 18.82 | 80   | 0.1204          | 0.9633   |
| 0.1226        | 20.0  | 85   | 0.0502          | 0.9633   |
| 0.1901        | 20.94 | 89   | 0.0188          | 1.0      |
| 0.1305        | 21.88 | 93   | 0.0244          | 0.9908   |
| 0.1695        | 22.82 | 97   | 0.0186          | 1.0      |
| 0.2682        | 24.0  | 102  | 0.0460          | 0.9817   |
| 0.1956        | 24.94 | 106  | 0.0328          | 0.9817   |
| 0.1651        | 25.88 | 110  | 0.0493          | 0.9817   |
| 0.1841        | 26.82 | 114  | 0.0168          | 1.0      |
| 0.1897        | 28.0  | 119  | 0.0139          | 1.0      |
| 0.2088        | 28.94 | 123  | 0.0195          | 1.0      |
| 0.1386        | 29.88 | 127  | 0.0483          | 0.9817   |
| 0.1544        | 30.82 | 131  | 0.0258          | 0.9817   |
| 0.1293        | 32.0  | 136  | 0.0461          | 0.9725   |
| 0.1696        | 32.94 | 140  | 0.0207          | 0.9908   |
| 0.1793        | 33.88 | 144  | 0.0182          | 1.0      |
| 0.1545        | 34.82 | 148  | 0.0361          | 0.9817   |
| 0.141         | 36.0  | 153  | 0.0455          | 0.9817   |
| 0.138         | 36.94 | 157  | 0.0175          | 0.9908   |
| 0.1382        | 37.88 | 161  | 0.0359          | 0.9817   |
| 0.163         | 38.82 | 165  | 0.0463          | 0.9817   |
| 0.1374        | 40.0  | 170  | 0.0153          | 0.9908   |
| 0.1993        | 40.94 | 174  | 0.0116          | 1.0      |
| 0.1471        | 41.88 | 178  | 0.0199          | 0.9817   |
| 0.1414        | 42.82 | 182  | 0.0330          | 0.9817   |
| 0.1494        | 44.0  | 187  | 0.0228          | 0.9817   |
| 0.1367        | 44.94 | 191  | 0.0174          | 0.9817   |
| 0.1529        | 45.88 | 195  | 0.0162          | 0.9817   |
| 0.1365        | 46.82 | 199  | 0.0153          | 0.9908   |
| 0.1301        | 47.06 | 200  | 0.0152          | 0.9908   |


### Framework versions

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

plant2 plant3