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# smids_1x_deit_small_adamax_001_fold4

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: 1.3725
- Accuracy: 0.8583

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.515         | 1.0   | 75   | 0.5041          | 0.8      |
| 0.5037        | 2.0   | 150  | 0.5053          | 0.79     |
| 0.2905        | 3.0   | 225  | 0.4325          | 0.8283   |
| 0.3469        | 4.0   | 300  | 0.4033          | 0.845    |
| 0.2428        | 5.0   | 375  | 0.5311          | 0.8033   |
| 0.2048        | 6.0   | 450  | 0.4711          | 0.8467   |
| 0.1912        | 7.0   | 525  | 0.5110          | 0.84     |
| 0.1617        | 8.0   | 600  | 0.4469          | 0.845    |
| 0.1268        | 9.0   | 675  | 0.6229          | 0.8483   |
| 0.0586        | 10.0  | 750  | 0.6742          | 0.8433   |
| 0.05          | 11.0  | 825  | 0.6876          | 0.8517   |
| 0.0724        | 12.0  | 900  | 0.6762          | 0.8633   |
| 0.0728        | 13.0  | 975  | 0.7911          | 0.8417   |
| 0.0259        | 14.0  | 1050 | 0.6721          | 0.84     |
| 0.0254        | 15.0  | 1125 | 0.7841          | 0.8517   |
| 0.0264        | 16.0  | 1200 | 0.9642          | 0.8383   |
| 0.0503        | 17.0  | 1275 | 0.9056          | 0.8483   |
| 0.0537        | 18.0  | 1350 | 1.0301          | 0.8517   |
| 0.0053        | 19.0  | 1425 | 0.9551          | 0.845    |
| 0.0045        | 20.0  | 1500 | 0.9526          | 0.8483   |
| 0.0133        | 21.0  | 1575 | 1.0780          | 0.8333   |
| 0.0123        | 22.0  | 1650 | 0.9370          | 0.8617   |
| 0.0051        | 23.0  | 1725 | 0.9638          | 0.855    |
| 0.0056        | 24.0  | 1800 | 0.9925          | 0.8517   |
| 0.0121        | 25.0  | 1875 | 1.0419          | 0.8483   |
| 0.0002        | 26.0  | 1950 | 1.0739          | 0.8567   |
| 0.0           | 27.0  | 2025 | 1.1470          | 0.8583   |
| 0.0068        | 28.0  | 2100 | 1.1576          | 0.8583   |
| 0.0055        | 29.0  | 2175 | 1.1500          | 0.8567   |
| 0.0           | 30.0  | 2250 | 1.1994          | 0.8533   |
| 0.0           | 31.0  | 2325 | 1.2151          | 0.8583   |
| 0.0           | 32.0  | 2400 | 1.2684          | 0.8567   |
| 0.0           | 33.0  | 2475 | 1.1310          | 0.8567   |
| 0.0           | 34.0  | 2550 | 1.1896          | 0.855    |
| 0.0           | 35.0  | 2625 | 1.2405          | 0.8567   |
| 0.0004        | 36.0  | 2700 | 1.2637          | 0.8567   |
| 0.0037        | 37.0  | 2775 | 1.2924          | 0.8567   |
| 0.0           | 38.0  | 2850 | 1.3058          | 0.855    |
| 0.0           | 39.0  | 2925 | 1.3179          | 0.855    |
| 0.0001        | 40.0  | 3000 | 1.3267          | 0.855    |
| 0.003         | 41.0  | 3075 | 1.3385          | 0.8583   |
| 0.0           | 42.0  | 3150 | 1.3471          | 0.8583   |
| 0.0           | 43.0  | 3225 | 1.3533          | 0.8583   |
| 0.0           | 44.0  | 3300 | 1.3593          | 0.8583   |
| 0.0           | 45.0  | 3375 | 1.3636          | 0.8583   |
| 0.0           | 46.0  | 3450 | 1.3666          | 0.8583   |
| 0.0           | 47.0  | 3525 | 1.3691          | 0.8583   |
| 0.0           | 48.0  | 3600 | 1.3710          | 0.8583   |
| 0.0           | 49.0  | 3675 | 1.3721          | 0.8583   |
| 0.0           | 50.0  | 3750 | 1.3725          | 0.8583   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8583333333333333, "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