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# hushem_5x_deit_tiny_adamax_00001_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: 1.0196
- Accuracy: 0.8293

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3464        | 1.0   | 28   | 1.2206          | 0.4390   |
| 1.038         | 2.0   | 56   | 1.1163          | 0.4390   |
| 0.9036        | 3.0   | 84   | 1.0326          | 0.5122   |
| 0.7256        | 4.0   | 112  | 0.9850          | 0.4634   |
| 0.6091        | 5.0   | 140  | 0.9299          | 0.5366   |
| 0.5118        | 6.0   | 168  | 0.8096          | 0.6098   |
| 0.3976        | 7.0   | 196  | 0.8337          | 0.6341   |
| 0.2983        | 8.0   | 224  | 0.8361          | 0.6829   |
| 0.2464        | 9.0   | 252  | 0.7489          | 0.6829   |
| 0.1797        | 10.0  | 280  | 0.7126          | 0.7317   |
| 0.155         | 11.0  | 308  | 0.7190          | 0.7317   |
| 0.1087        | 12.0  | 336  | 0.7349          | 0.7561   |
| 0.0817        | 13.0  | 364  | 0.6756          | 0.7805   |
| 0.0808        | 14.0  | 392  | 0.7587          | 0.7561   |
| 0.0526        | 15.0  | 420  | 0.6534          | 0.7805   |
| 0.0415        | 16.0  | 448  | 0.7396          | 0.7805   |
| 0.0249        | 17.0  | 476  | 0.7772          | 0.8049   |
| 0.0224        | 18.0  | 504  | 0.7783          | 0.8049   |
| 0.016         | 19.0  | 532  | 0.8153          | 0.7805   |
| 0.0121        | 20.0  | 560  | 0.8052          | 0.8049   |
| 0.0082        | 21.0  | 588  | 0.8047          | 0.8049   |
| 0.0059        | 22.0  | 616  | 0.8544          | 0.8049   |
| 0.0042        | 23.0  | 644  | 0.9271          | 0.7805   |
| 0.0032        | 24.0  | 672  | 0.8999          | 0.8049   |
| 0.0029        | 25.0  | 700  | 0.9068          | 0.8293   |
| 0.0025        | 26.0  | 728  | 0.9094          | 0.8293   |
| 0.0022        | 27.0  | 756  | 0.9291          | 0.8293   |
| 0.0019        | 28.0  | 784  | 0.9347          | 0.8293   |
| 0.0016        | 29.0  | 812  | 0.9448          | 0.8293   |
| 0.0016        | 30.0  | 840  | 0.9586          | 0.8293   |
| 0.0015        | 31.0  | 868  | 0.9704          | 0.8293   |
| 0.0013        | 32.0  | 896  | 0.9735          | 0.8293   |
| 0.0013        | 33.0  | 924  | 0.9776          | 0.8293   |
| 0.0012        | 34.0  | 952  | 0.9829          | 0.8293   |
| 0.0011        | 35.0  | 980  | 0.9923          | 0.8293   |
| 0.0011        | 36.0  | 1008 | 0.9922          | 0.8293   |
| 0.001         | 37.0  | 1036 | 0.9983          | 0.8293   |
| 0.001         | 38.0  | 1064 | 1.0035          | 0.8293   |
| 0.0009        | 39.0  | 1092 | 0.9985          | 0.8293   |
| 0.0009        | 40.0  | 1120 | 1.0064          | 0.8293   |
| 0.0009        | 41.0  | 1148 | 1.0089          | 0.8293   |
| 0.0008        | 42.0  | 1176 | 1.0130          | 0.8293   |
| 0.0008        | 43.0  | 1204 | 1.0152          | 0.8293   |
| 0.0009        | 44.0  | 1232 | 1.0185          | 0.8293   |
| 0.0009        | 45.0  | 1260 | 1.0165          | 0.8293   |
| 0.0009        | 46.0  | 1288 | 1.0180          | 0.8293   |
| 0.0008        | 47.0  | 1316 | 1.0182          | 0.8293   |
| 0.0008        | 48.0  | 1344 | 1.0196          | 0.8293   |
| 0.0008        | 49.0  | 1372 | 1.0196          | 0.8293   |
| 0.0008        | 50.0  | 1400 | 1.0196          | 0.8293   |


### 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_00001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8292682926829268, "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