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# lettuce-npk-vit

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: 0.1492
- Accuracy: 0.9524

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.1633        | 0.992   | 31   | 1.1239          | 0.8571   |
| 0.4802        | 1.984   | 62   | 0.4213          | 0.9048   |
| 0.1386        | 2.976   | 93   | 0.2501          | 0.9524   |
| 0.1003        | 4.0     | 125  | 0.1879          | 0.9524   |
| 0.0871        | 4.992   | 156  | 0.3482          | 0.8571   |
| 0.0702        | 5.984   | 187  | 0.2048          | 0.9524   |
| 0.0594        | 6.976   | 218  | 0.2824          | 0.9048   |
| 0.0425        | 8.0     | 250  | 0.2567          | 0.9524   |
| 0.0398        | 8.992   | 281  | 0.3363          | 0.8571   |
| 0.0348        | 9.984   | 312  | 0.2518          | 0.9524   |
| 0.0411        | 10.9760 | 343  | 0.0369          | 1.0      |
| 0.0445        | 12.0    | 375  | 0.2288          | 0.9524   |
| 0.0353        | 12.992  | 406  | 0.2364          | 0.8571   |
| 0.0384        | 13.984  | 437  | 0.2255          | 0.9524   |
| 0.0331        | 14.9760 | 468  | 0.0572          | 1.0      |
| 0.0252        | 16.0    | 500  | 0.2103          | 0.9524   |
| 0.0337        | 16.992  | 531  | 0.0295          | 1.0      |
| 0.0302        | 17.984  | 562  | 0.2805          | 0.9048   |
| 0.0328        | 18.976  | 593  | 0.2127          | 0.9524   |
| 0.0315        | 19.84   | 620  | 0.1492          | 0.9524   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1

-k -n -p fn