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# smids_1x_deit_tiny_adamax_001_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: 1.0690
- Accuracy: 0.855

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7211        | 1.0   | 75   | 0.5344          | 0.7933   |
| 0.4907        | 2.0   | 150  | 0.4899          | 0.8217   |
| 0.4082        | 3.0   | 225  | 0.3985          | 0.8433   |
| 0.5374        | 4.0   | 300  | 0.4992          | 0.7867   |
| 0.3999        | 5.0   | 375  | 0.4245          | 0.8317   |
| 0.2788        | 6.0   | 450  | 0.4489          | 0.8333   |
| 0.2587        | 7.0   | 525  | 0.4635          | 0.8433   |
| 0.4094        | 8.0   | 600  | 0.4633          | 0.8517   |
| 0.2907        | 9.0   | 675  | 0.3956          | 0.855    |
| 0.1834        | 10.0  | 750  | 0.5651          | 0.8483   |
| 0.1936        | 11.0  | 825  | 0.5738          | 0.8317   |
| 0.0829        | 12.0  | 900  | 0.6121          | 0.8517   |
| 0.1614        | 13.0  | 975  | 0.7303          | 0.8317   |
| 0.1046        | 14.0  | 1050 | 0.6603          | 0.8333   |
| 0.0809        | 15.0  | 1125 | 0.6576          | 0.835    |
| 0.0884        | 16.0  | 1200 | 0.7089          | 0.8433   |
| 0.0489        | 17.0  | 1275 | 0.6901          | 0.855    |
| 0.1163        | 18.0  | 1350 | 0.9715          | 0.8083   |
| 0.0364        | 19.0  | 1425 | 0.8902          | 0.8417   |
| 0.0696        | 20.0  | 1500 | 0.9452          | 0.8317   |
| 0.0058        | 21.0  | 1575 | 1.0231          | 0.845    |
| 0.0448        | 22.0  | 1650 | 0.8657          | 0.855    |
| 0.0768        | 23.0  | 1725 | 1.0329          | 0.8367   |
| 0.0352        | 24.0  | 1800 | 0.8052          | 0.8467   |
| 0.0563        | 25.0  | 1875 | 0.7949          | 0.84     |
| 0.0082        | 26.0  | 1950 | 1.0964          | 0.8283   |
| 0.0281        | 27.0  | 2025 | 1.0752          | 0.8283   |
| 0.0273        | 28.0  | 2100 | 0.9073          | 0.8567   |
| 0.0259        | 29.0  | 2175 | 0.9898          | 0.8467   |
| 0.0073        | 30.0  | 2250 | 0.9057          | 0.855    |
| 0.0002        | 31.0  | 2325 | 1.1211          | 0.8333   |
| 0.0001        | 32.0  | 2400 | 0.9915          | 0.8533   |
| 0.0124        | 33.0  | 2475 | 1.0550          | 0.8517   |
| 0.0001        | 34.0  | 2550 | 1.0250          | 0.8533   |
| 0.0062        | 35.0  | 2625 | 1.0105          | 0.8533   |
| 0.0001        | 36.0  | 2700 | 1.0089          | 0.8533   |
| 0.0047        | 37.0  | 2775 | 1.0162          | 0.855    |
| 0.0           | 38.0  | 2850 | 1.0334          | 0.85     |
| 0.0           | 39.0  | 2925 | 1.0457          | 0.85     |
| 0.0           | 40.0  | 3000 | 1.0361          | 0.8567   |
| 0.0039        | 41.0  | 3075 | 1.0596          | 0.855    |
| 0.0           | 42.0  | 3150 | 1.0411          | 0.8567   |
| 0.0081        | 43.0  | 3225 | 1.0513          | 0.855    |
| 0.0001        | 44.0  | 3300 | 1.0505          | 0.855    |
| 0.0027        | 45.0  | 3375 | 1.0576          | 0.8583   |
| 0.0           | 46.0  | 3450 | 1.0612          | 0.8583   |
| 0.0065        | 47.0  | 3525 | 1.0629          | 0.8567   |
| 0.0058        | 48.0  | 3600 | 1.0684          | 0.8567   |
| 0.0           | 49.0  | 3675 | 1.0680          | 0.8567   |
| 0.0041        | 50.0  | 3750 | 1.0690          | 0.855    |


### 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_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": 0.855, "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