
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-base-patch16-224-Trial006_007_008-YEL_STEM

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: 0.0487
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7096        | 0.95  | 5    | 0.6879          | 0.5507   |
| 0.6238        | 1.9   | 10   | 0.5505          | 0.7681   |
| 0.4679        | 2.86  | 15   | 0.4054          | 0.9130   |
| 0.3643        | 4.0   | 21   | 0.2855          | 0.8841   |
| 0.3742        | 4.95  | 26   | 0.1808          | 0.9420   |
| 0.2924        | 5.9   | 31   | 0.1566          | 0.9420   |
| 0.2591        | 6.86  | 36   | 0.2318          | 0.8841   |
| 0.3206        | 8.0   | 42   | 0.3704          | 0.8261   |
| 0.1952        | 8.95  | 47   | 0.2086          | 0.9130   |
| 0.2185        | 9.9   | 52   | 0.1194          | 0.9565   |
| 0.2045        | 10.86 | 57   | 0.1291          | 0.9420   |
| 0.2793        | 12.0  | 63   | 0.0912          | 0.9565   |
| 0.2701        | 12.95 | 68   | 0.1109          | 0.9420   |
| 0.266         | 13.9  | 73   | 0.0927          | 0.9565   |
| 0.1964        | 14.86 | 78   | 0.0575          | 0.9710   |
| 0.218         | 16.0  | 84   | 0.0378          | 0.9855   |
| 0.2894        | 16.95 | 89   | 0.0659          | 0.9710   |
| 0.171         | 17.9  | 94   | 0.0706          | 0.9710   |
| 0.1871        | 18.86 | 99   | 0.0845          | 0.9565   |
| 0.2023        | 20.0  | 105  | 0.0487          | 1.0      |
| 0.1707        | 20.95 | 110  | 0.0496          | 0.9710   |
| 0.1741        | 21.9  | 115  | 0.1078          | 0.9420   |
| 0.1391        | 22.86 | 120  | 0.0740          | 0.9565   |
| 0.1892        | 24.0  | 126  | 0.0581          | 0.9710   |
| 0.1488        | 24.95 | 131  | 0.0833          | 0.9710   |
| 0.2089        | 25.9  | 136  | 0.0375          | 0.9855   |
| 0.1922        | 26.86 | 141  | 0.0267          | 0.9855   |
| 0.2222        | 28.0  | 147  | 0.0196          | 1.0      |
| 0.1567        | 28.95 | 152  | 0.0213          | 0.9855   |
| 0.2429        | 29.9  | 157  | 0.0263          | 1.0      |
| 0.1175        | 30.86 | 162  | 0.0304          | 0.9855   |
| 0.1492        | 32.0  | 168  | 0.0291          | 1.0      |
| 0.1401        | 32.95 | 173  | 0.0226          | 0.9855   |
| 0.1757        | 33.9  | 178  | 0.0302          | 0.9855   |
| 0.1773        | 34.86 | 183  | 0.0220          | 0.9855   |
| 0.193         | 36.0  | 189  | 0.0349          | 0.9855   |
| 0.1634        | 36.95 | 194  | 0.0483          | 0.9855   |
| 0.1847        | 37.9  | 199  | 0.0391          | 0.9855   |
| 0.1632        | 38.86 | 204  | 0.0457          | 0.9855   |
| 0.1349        | 40.0  | 210  | 0.0366          | 0.9855   |
| 0.1935        | 40.95 | 215  | 0.0301          | 0.9855   |
| 0.1461        | 41.9  | 220  | 0.0291          | 0.9855   |
| 0.2092        | 42.86 | 225  | 0.0367          | 0.9855   |
| 0.1552        | 44.0  | 231  | 0.0296          | 0.9855   |
| 0.2361        | 44.95 | 236  | 0.0323          | 0.9855   |
| 0.1161        | 45.9  | 241  | 0.0348          | 0.9855   |
| 0.127         | 46.86 | 246  | 0.0365          | 0.9855   |
| 0.186         | 47.62 | 250  | 0.0374          | 0.9855   |


### 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-Trial006_007_008-YEL_STEM", "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