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# vit-base-patch16-224-Trial007-YEL_STEM4

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: 0.1348
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.778         | 0.8   | 1    | 0.7723          | 0.4286   |
| 0.8135        | 1.6   | 2    | 0.6793          | 0.6429   |
| 0.6802        | 2.4   | 3    | 0.5444          | 0.8571   |
| 0.4538        | 4.0   | 5    | 0.3234          | 0.9643   |
| 0.3745        | 4.8   | 6    | 0.2094          | 0.9643   |
| 0.2472        | 5.6   | 7    | 0.1348          | 1.0      |
| 0.1934        | 6.4   | 8    | 0.0836          | 1.0      |
| 0.2277        | 8.0   | 10   | 0.0498          | 1.0      |
| 0.1106        | 8.8   | 11   | 0.0540          | 0.9643   |
| 0.1109        | 9.6   | 12   | 0.0505          | 0.9643   |
| 0.0999        | 10.4  | 13   | 0.0319          | 1.0      |
| 0.1259        | 12.0  | 15   | 0.0099          | 1.0      |
| 0.1245        | 12.8  | 16   | 0.0056          | 1.0      |
| 0.0548        | 13.6  | 17   | 0.0038          | 1.0      |
| 0.1065        | 14.4  | 18   | 0.0029          | 1.0      |
| 0.0624        | 16.0  | 20   | 0.0020          | 1.0      |
| 0.0578        | 16.8  | 21   | 0.0016          | 1.0      |
| 0.0584        | 17.6  | 22   | 0.0014          | 1.0      |
| 0.0764        | 18.4  | 23   | 0.0012          | 1.0      |
| 0.0541        | 20.0  | 25   | 0.0010          | 1.0      |
| 0.0444        | 20.8  | 26   | 0.0009          | 1.0      |
| 0.0429        | 21.6  | 27   | 0.0008          | 1.0      |
| 0.0632        | 22.4  | 28   | 0.0008          | 1.0      |
| 0.0521        | 24.0  | 30   | 0.0007          | 1.0      |
| 0.08          | 24.8  | 31   | 0.0007          | 1.0      |
| 0.0829        | 25.6  | 32   | 0.0007          | 1.0      |
| 0.0449        | 26.4  | 33   | 0.0006          | 1.0      |
| 0.0526        | 28.0  | 35   | 0.0006          | 1.0      |
| 0.1084        | 28.8  | 36   | 0.0006          | 1.0      |
| 0.0327        | 29.6  | 37   | 0.0006          | 1.0      |
| 0.0916        | 30.4  | 38   | 0.0005          | 1.0      |
| 0.0472        | 32.0  | 40   | 0.0005          | 1.0      |
| 0.0764        | 32.8  | 41   | 0.0005          | 1.0      |
| 0.0603        | 33.6  | 42   | 0.0005          | 1.0      |
| 0.0375        | 34.4  | 43   | 0.0005          | 1.0      |
| 0.0572        | 36.0  | 45   | 0.0005          | 1.0      |
| 0.0587        | 36.8  | 46   | 0.0005          | 1.0      |
| 0.0468        | 37.6  | 47   | 0.0005          | 1.0      |
| 0.0566        | 38.4  | 48   | 0.0005          | 1.0      |
| 0.0471        | 40.0  | 50   | 0.0005          | 1.0      |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "model-index": [{"name": "vit-base-patch16-224-Trial007-YEL_STEM4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 1.0, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us