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# smids_1x_deit_tiny_adamax_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: 0.8318
- Accuracy: 0.8767

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4622        | 1.0   | 75   | 0.3902          | 0.85     |
| 0.3997        | 2.0   | 150  | 0.3259          | 0.8767   |
| 0.1811        | 3.0   | 225  | 0.3681          | 0.8767   |
| 0.2239        | 4.0   | 300  | 0.3692          | 0.8717   |
| 0.1061        | 5.0   | 375  | 0.3361          | 0.89     |
| 0.0643        | 6.0   | 450  | 0.4246          | 0.8867   |
| 0.0349        | 7.0   | 525  | 0.5503          | 0.865    |
| 0.0577        | 8.0   | 600  | 0.4923          | 0.89     |
| 0.0047        | 9.0   | 675  | 0.6463          | 0.875    |
| 0.0074        | 10.0  | 750  | 0.6530          | 0.8683   |
| 0.037         | 11.0  | 825  | 0.6041          | 0.8767   |
| 0.0089        | 12.0  | 900  | 0.6572          | 0.8833   |
| 0.0191        | 13.0  | 975  | 0.7128          | 0.8867   |
| 0.0365        | 14.0  | 1050 | 0.8168          | 0.8733   |
| 0.0272        | 15.0  | 1125 | 0.7575          | 0.875    |
| 0.0001        | 16.0  | 1200 | 0.7279          | 0.8817   |
| 0.0112        | 17.0  | 1275 | 0.7893          | 0.885    |
| 0.0208        | 18.0  | 1350 | 0.8683          | 0.8667   |
| 0.0094        | 19.0  | 1425 | 0.8173          | 0.875    |
| 0.0001        | 20.0  | 1500 | 0.8675          | 0.8633   |
| 0.005         | 21.0  | 1575 | 0.8404          | 0.8633   |
| 0.0089        | 22.0  | 1650 | 0.8394          | 0.8633   |
| 0.0106        | 23.0  | 1725 | 0.7646          | 0.8733   |
| 0.0           | 24.0  | 1800 | 0.7970          | 0.8667   |
| 0.0166        | 25.0  | 1875 | 0.7834          | 0.8767   |
| 0.0           | 26.0  | 1950 | 0.7904          | 0.8833   |
| 0.0062        | 27.0  | 2025 | 0.8106          | 0.8667   |
| 0.0107        | 28.0  | 2100 | 0.7803          | 0.8767   |
| 0.0105        | 29.0  | 2175 | 0.7751          | 0.875    |
| 0.0047        | 30.0  | 2250 | 0.7593          | 0.875    |
| 0.0           | 31.0  | 2325 | 0.8560          | 0.8733   |
| 0.0           | 32.0  | 2400 | 0.7908          | 0.87     |
| 0.0066        | 33.0  | 2475 | 0.8221          | 0.875    |
| 0.0           | 34.0  | 2550 | 0.8079          | 0.8733   |
| 0.0052        | 35.0  | 2625 | 0.8173          | 0.875    |
| 0.0           | 36.0  | 2700 | 0.8258          | 0.8733   |
| 0.0045        | 37.0  | 2775 | 0.8236          | 0.8733   |
| 0.0           | 38.0  | 2850 | 0.8199          | 0.875    |
| 0.0           | 39.0  | 2925 | 0.8205          | 0.8733   |
| 0.0           | 40.0  | 3000 | 0.8239          | 0.8733   |
| 0.0036        | 41.0  | 3075 | 0.8262          | 0.8767   |
| 0.0           | 42.0  | 3150 | 0.8270          | 0.875    |
| 0.0074        | 43.0  | 3225 | 0.8280          | 0.875    |
| 0.0           | 44.0  | 3300 | 0.8301          | 0.875    |
| 0.0026        | 45.0  | 3375 | 0.8317          | 0.875    |
| 0.0           | 46.0  | 3450 | 0.8313          | 0.8767   |
| 0.0057        | 47.0  | 3525 | 0.8305          | 0.875    |
| 0.0054        | 48.0  | 3600 | 0.8318          | 0.8767   |
| 0.0           | 49.0  | 3675 | 0.8319          | 0.8767   |
| 0.0042        | 50.0  | 3750 | 0.8318          | 0.8767   |


### 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-tiny-patch16-224", "model-index": [{"name": "smids_1x_deit_tiny_adamax_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": 0.8766666666666667, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors 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