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# vit-base-patch16-224-Trial008-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: 0.1024
- 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: 30
- eval_batch_size: 30
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 120
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7598        | 0.67  | 1    | 0.6968          | 0.6471   |
| 0.7294        | 2.0   | 3    | 0.7662          | 0.4706   |
| 0.6662        | 2.67  | 4    | 0.7196          | 0.5882   |
| 0.5662        | 4.0   | 6    | 0.3941          | 0.8235   |
| 0.4781        | 4.67  | 7    | 0.3458          | 0.8235   |
| 0.3259        | 6.0   | 9    | 0.1699          | 0.9412   |
| 0.2903        | 6.67  | 10   | 0.1024          | 1.0      |
| 0.2206        | 8.0   | 12   | 0.0788          | 1.0      |
| 0.3215        | 8.67  | 13   | 0.0414          | 1.0      |
| 0.1741        | 10.0  | 15   | 0.0218          | 1.0      |
| 0.2222        | 10.67 | 16   | 0.0207          | 1.0      |
| 0.1534        | 12.0  | 18   | 0.0128          | 1.0      |
| 0.273         | 12.67 | 19   | 0.0103          | 1.0      |
| 0.2021        | 14.0  | 21   | 0.0080          | 1.0      |
| 0.2193        | 14.67 | 22   | 0.0100          | 1.0      |
| 0.2132        | 16.0  | 24   | 0.0247          | 1.0      |
| 0.2163        | 16.67 | 25   | 0.0266          | 1.0      |
| 0.1626        | 18.0  | 27   | 0.0101          | 1.0      |
| 0.2492        | 18.67 | 28   | 0.0059          | 1.0      |
| 0.1308        | 20.0  | 30   | 0.0056          | 1.0      |
| 0.2144        | 20.67 | 31   | 0.0060          | 1.0      |
| 0.1389        | 22.0  | 33   | 0.0044          | 1.0      |
| 0.2548        | 22.67 | 34   | 0.0040          | 1.0      |
| 0.1324        | 24.0  | 36   | 0.0037          | 1.0      |
| 0.1958        | 24.67 | 37   | 0.0036          | 1.0      |
| 0.2476        | 26.0  | 39   | 0.0035          | 1.0      |
| 0.1439        | 26.67 | 40   | 0.0033          | 1.0      |
| 0.1202        | 28.0  | 42   | 0.0030          | 1.0      |
| 0.1368        | 28.67 | 43   | 0.0028          | 1.0      |
| 0.1016        | 30.0  | 45   | 0.0027          | 1.0      |
| 0.1282        | 30.67 | 46   | 0.0027          | 1.0      |
| 0.1128        | 32.0  | 48   | 0.0026          | 1.0      |
| 0.2366        | 32.67 | 49   | 0.0026          | 1.0      |
| 0.1727        | 33.33 | 50   | 0.0026          | 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-Trial008-YEL_STEM2", "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