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# smids_1x_deit_small_adamax_001_fold5

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0002
- Accuracy: 0.86

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6434        | 1.0   | 75   | 0.5267          | 0.795    |
| 0.4681        | 2.0   | 150  | 0.4240          | 0.82     |
| 0.3802        | 3.0   | 225  | 0.4300          | 0.8317   |
| 0.3978        | 4.0   | 300  | 0.4417          | 0.815    |
| 0.2851        | 5.0   | 375  | 0.4444          | 0.82     |
| 0.1694        | 6.0   | 450  | 0.3647          | 0.87     |
| 0.1978        | 7.0   | 525  | 0.4075          | 0.85     |
| 0.3005        | 8.0   | 600  | 0.3919          | 0.8533   |
| 0.1464        | 9.0   | 675  | 0.5040          | 0.85     |
| 0.0679        | 10.0  | 750  | 0.4768          | 0.8683   |
| 0.1428        | 11.0  | 825  | 0.5770          | 0.8367   |
| 0.0515        | 12.0  | 900  | 0.7151          | 0.8483   |
| 0.0525        | 13.0  | 975  | 0.6841          | 0.8433   |
| 0.0836        | 14.0  | 1050 | 0.6721          | 0.8583   |
| 0.0701        | 15.0  | 1125 | 0.7481          | 0.835    |
| 0.0512        | 16.0  | 1200 | 0.7462          | 0.8383   |
| 0.0331        | 17.0  | 1275 | 0.6909          | 0.86     |
| 0.0421        | 18.0  | 1350 | 0.8979          | 0.855    |
| 0.0249        | 19.0  | 1425 | 0.6741          | 0.865    |
| 0.0085        | 20.0  | 1500 | 0.8222          | 0.8483   |
| 0.0231        | 21.0  | 1575 | 0.6427          | 0.87     |
| 0.0092        | 22.0  | 1650 | 0.8231          | 0.8533   |
| 0.015         | 23.0  | 1725 | 0.8772          | 0.8533   |
| 0.002         | 24.0  | 1800 | 0.7754          | 0.86     |
| 0.0148        | 25.0  | 1875 | 0.8250          | 0.8733   |
| 0.004         | 26.0  | 1950 | 0.8667          | 0.8717   |
| 0.0153        | 27.0  | 2025 | 0.8197          | 0.8717   |
| 0.0089        | 28.0  | 2100 | 0.9170          | 0.8617   |
| 0.007         | 29.0  | 2175 | 0.9333          | 0.8583   |
| 0.0035        | 30.0  | 2250 | 0.8964          | 0.8667   |
| 0.0           | 31.0  | 2325 | 0.9173          | 0.8567   |
| 0.0           | 32.0  | 2400 | 0.9057          | 0.8617   |
| 0.0063        | 33.0  | 2475 | 0.9409          | 0.8667   |
| 0.0           | 34.0  | 2550 | 0.9412          | 0.8583   |
| 0.005         | 35.0  | 2625 | 0.9293          | 0.865    |
| 0.0           | 36.0  | 2700 | 0.9399          | 0.865    |
| 0.004         | 37.0  | 2775 | 0.9622          | 0.8683   |
| 0.001         | 38.0  | 2850 | 0.9655          | 0.8583   |
| 0.0           | 39.0  | 2925 | 0.9962          | 0.855    |
| 0.0           | 40.0  | 3000 | 0.9897          | 0.8567   |
| 0.0034        | 41.0  | 3075 | 0.9959          | 0.855    |
| 0.0           | 42.0  | 3150 | 0.9928          | 0.86     |
| 0.0077        | 43.0  | 3225 | 0.9873          | 0.8617   |
| 0.0           | 44.0  | 3300 | 0.9978          | 0.8583   |
| 0.0025        | 45.0  | 3375 | 0.9949          | 0.8617   |
| 0.0           | 46.0  | 3450 | 0.9977          | 0.8567   |
| 0.006         | 47.0  | 3525 | 0.9987          | 0.8567   |
| 0.0055        | 48.0  | 3600 | 1.0022          | 0.855    |
| 0.0           | 49.0  | 3675 | 1.0012          | 0.8583   |
| 0.0043        | 50.0  | 3750 | 1.0002          | 0.86     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-small-patch16-224", "model-index": [{"name": "smids_1x_deit_small_adamax_001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.86, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us