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# hushem_40x_deit_tiny_rms_0001_fold5

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8832
- Accuracy: 0.8780

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1509        | 1.0   | 220   | 0.5608          | 0.8537   |
| 0.0292        | 2.0   | 440   | 0.1504          | 0.9512   |
| 0.1009        | 3.0   | 660   | 0.7468          | 0.8537   |
| 0.011         | 4.0   | 880   | 0.6340          | 0.7805   |
| 0.0031        | 5.0   | 1100  | 0.8446          | 0.8293   |
| 0.0646        | 6.0   | 1320  | 1.0420          | 0.8537   |
| 0.0678        | 7.0   | 1540  | 0.6521          | 0.8293   |
| 0.0002        | 8.0   | 1760  | 1.1011          | 0.8537   |
| 0.0677        | 9.0   | 1980  | 1.2605          | 0.8049   |
| 0.0002        | 10.0  | 2200  | 0.4029          | 0.9024   |
| 0.0011        | 11.0  | 2420  | 0.5279          | 0.9512   |
| 0.0002        | 12.0  | 2640  | 0.5883          | 0.9268   |
| 0.0801        | 13.0  | 2860  | 1.0161          | 0.8293   |
| 0.0           | 14.0  | 3080  | 0.7618          | 0.9024   |
| 0.0           | 15.0  | 3300  | 0.7876          | 0.8293   |
| 0.0144        | 16.0  | 3520  | 0.6802          | 0.8780   |
| 0.0032        | 17.0  | 3740  | 0.2440          | 0.9268   |
| 0.0           | 18.0  | 3960  | 0.4384          | 0.8293   |
| 0.0           | 19.0  | 4180  | 0.6787          | 0.8537   |
| 0.0           | 20.0  | 4400  | 0.6527          | 0.8293   |
| 0.0           | 21.0  | 4620  | 0.6512          | 0.8537   |
| 0.0           | 22.0  | 4840  | 0.6749          | 0.8537   |
| 0.0           | 23.0  | 5060  | 0.6838          | 0.8537   |
| 0.0           | 24.0  | 5280  | 0.7554          | 0.8537   |
| 0.0           | 25.0  | 5500  | 0.8097          | 0.8780   |
| 0.0           | 26.0  | 5720  | 0.8183          | 0.8780   |
| 0.0           | 27.0  | 5940  | 0.8490          | 0.8780   |
| 0.0           | 28.0  | 6160  | 0.9053          | 0.8537   |
| 0.0           | 29.0  | 6380  | 0.9213          | 0.8537   |
| 0.0           | 30.0  | 6600  | 0.9237          | 0.8780   |
| 0.0           | 31.0  | 6820  | 0.9293          | 0.8537   |
| 0.0           | 32.0  | 7040  | 0.9309          | 0.8780   |
| 0.0           | 33.0  | 7260  | 0.9345          | 0.8780   |
| 0.0           | 34.0  | 7480  | 0.9273          | 0.8780   |
| 0.0           | 35.0  | 7700  | 0.9432          | 0.8780   |
| 0.0           | 36.0  | 7920  | 0.9371          | 0.8780   |
| 0.0           | 37.0  | 8140  | 0.9224          | 0.9024   |
| 0.0           | 38.0  | 8360  | 0.9410          | 0.8780   |
| 0.0           | 39.0  | 8580  | 0.9241          | 0.8780   |
| 0.0           | 40.0  | 8800  | 0.9144          | 0.8780   |
| 0.0           | 41.0  | 9020  | 0.9167          | 0.8780   |
| 0.0           | 42.0  | 9240  | 0.8992          | 0.8780   |
| 0.0           | 43.0  | 9460  | 0.9050          | 0.8780   |
| 0.0           | 44.0  | 9680  | 0.8956          | 0.8780   |
| 0.0           | 45.0  | 9900  | 0.8902          | 0.8780   |
| 0.0           | 46.0  | 10120 | 0.8925          | 0.8780   |
| 0.0           | 47.0  | 10340 | 0.8847          | 0.8780   |
| 0.0           | 48.0  | 10560 | 0.8839          | 0.8780   |
| 0.0           | 49.0  | 10780 | 0.8833          | 0.8780   |
| 0.0           | 50.0  | 11000 | 0.8832          | 0.8780   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "hushem_40x_deit_tiny_rms_0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8780487804878049, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us