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# hushem_5x_deit_tiny_adamax_001_fold3

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: 1.8507
- Accuracy: 0.7209

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4597        | 1.0   | 28   | 1.3552          | 0.3256   |
| 1.2609        | 2.0   | 56   | 0.9015          | 0.6744   |
| 1.1559        | 3.0   | 84   | 2.3181          | 0.3256   |
| 1.0822        | 4.0   | 112  | 1.6592          | 0.4186   |
| 1.0553        | 5.0   | 140  | 0.9222          | 0.4651   |
| 0.9651        | 6.0   | 168  | 0.7306          | 0.7442   |
| 0.9771        | 7.0   | 196  | 0.7827          | 0.6279   |
| 0.9016        | 8.0   | 224  | 0.9874          | 0.5581   |
| 0.8187        | 9.0   | 252  | 1.0233          | 0.5349   |
| 0.8405        | 10.0  | 280  | 0.6414          | 0.7674   |
| 0.7808        | 11.0  | 308  | 0.6637          | 0.6977   |
| 0.8152        | 12.0  | 336  | 0.5374          | 0.8605   |
| 0.8044        | 13.0  | 364  | 0.5684          | 0.7442   |
| 0.7275        | 14.0  | 392  | 0.6622          | 0.8140   |
| 0.6931        | 15.0  | 420  | 0.7767          | 0.7209   |
| 0.691         | 16.0  | 448  | 0.5520          | 0.7674   |
| 0.7585        | 17.0  | 476  | 0.6770          | 0.7674   |
| 0.6303        | 18.0  | 504  | 0.6834          | 0.7442   |
| 0.6578        | 19.0  | 532  | 0.7776          | 0.6977   |
| 0.4934        | 20.0  | 560  | 1.1067          | 0.7442   |
| 0.5397        | 21.0  | 588  | 0.7250          | 0.7674   |
| 0.5586        | 22.0  | 616  | 0.9824          | 0.6047   |
| 0.4808        | 23.0  | 644  | 0.9582          | 0.7442   |
| 0.4823        | 24.0  | 672  | 0.9114          | 0.6279   |
| 0.4124        | 25.0  | 700  | 1.1614          | 0.7209   |
| 0.3991        | 26.0  | 728  | 1.3579          | 0.6279   |
| 0.5138        | 27.0  | 756  | 1.5915          | 0.6512   |
| 0.3857        | 28.0  | 784  | 0.6799          | 0.8140   |
| 0.3797        | 29.0  | 812  | 1.1771          | 0.7907   |
| 0.3781        | 30.0  | 840  | 0.9809          | 0.7674   |
| 0.3225        | 31.0  | 868  | 0.7120          | 0.8140   |
| 0.3017        | 32.0  | 896  | 0.9984          | 0.7674   |
| 0.2468        | 33.0  | 924  | 1.0271          | 0.7674   |
| 0.1651        | 34.0  | 952  | 1.2194          | 0.7674   |
| 0.254         | 35.0  | 980  | 1.2984          | 0.7907   |
| 0.1644        | 36.0  | 1008 | 1.3708          | 0.7674   |
| 0.1972        | 37.0  | 1036 | 1.6461          | 0.7209   |
| 0.1252        | 38.0  | 1064 | 1.8473          | 0.7442   |
| 0.1252        | 39.0  | 1092 | 1.5823          | 0.7209   |
| 0.4334        | 40.0  | 1120 | 1.7311          | 0.7209   |
| 0.1029        | 41.0  | 1148 | 1.7390          | 0.7674   |
| 0.0992        | 42.0  | 1176 | 1.6959          | 0.7907   |
| 0.0993        | 43.0  | 1204 | 1.9237          | 0.7442   |
| 0.0435        | 44.0  | 1232 | 1.8569          | 0.7442   |
| 0.054         | 45.0  | 1260 | 1.8007          | 0.7907   |
| 0.0678        | 46.0  | 1288 | 1.8496          | 0.7442   |
| 0.0576        | 47.0  | 1316 | 1.8145          | 0.7442   |
| 0.0232        | 48.0  | 1344 | 1.8497          | 0.7209   |
| 0.0393        | 49.0  | 1372 | 1.8507          | 0.7209   |
| 0.0213        | 50.0  | 1400 | 1.8507          | 0.7209   |


### 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": "hushem_5x_deit_tiny_adamax_001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7209302325581395, "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