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# hushem_5x_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: 2.7115
- Accuracy: 0.6585

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4348        | 1.0   | 28   | 1.3734          | 0.2439   |
| 1.3624        | 2.0   | 56   | 1.4229          | 0.2683   |
| 1.1348        | 3.0   | 84   | 1.1315          | 0.3902   |
| 0.9863        | 4.0   | 112  | 1.0099          | 0.6829   |
| 0.9002        | 5.0   | 140  | 0.8153          | 0.7317   |
| 0.8747        | 6.0   | 168  | 0.8078          | 0.7317   |
| 0.7431        | 7.0   | 196  | 0.8202          | 0.7073   |
| 0.7236        | 8.0   | 224  | 0.6730          | 0.7073   |
| 0.7214        | 9.0   | 252  | 0.7811          | 0.6829   |
| 0.7661        | 10.0  | 280  | 0.8373          | 0.6341   |
| 0.6997        | 11.0  | 308  | 0.7829          | 0.7073   |
| 0.5964        | 12.0  | 336  | 0.9580          | 0.5366   |
| 0.601         | 13.0  | 364  | 0.8593          | 0.6341   |
| 0.4989        | 14.0  | 392  | 0.8291          | 0.7317   |
| 0.484         | 15.0  | 420  | 0.8268          | 0.7317   |
| 0.3579        | 16.0  | 448  | 0.8735          | 0.6585   |
| 0.3201        | 17.0  | 476  | 1.3019          | 0.6341   |
| 0.2054        | 18.0  | 504  | 1.2022          | 0.6829   |
| 0.2162        | 19.0  | 532  | 1.3723          | 0.6098   |
| 0.2359        | 20.0  | 560  | 2.1538          | 0.5854   |
| 0.1213        | 21.0  | 588  | 1.4495          | 0.6829   |
| 0.1657        | 22.0  | 616  | 1.5861          | 0.6341   |
| 0.2091        | 23.0  | 644  | 1.3652          | 0.6585   |
| 0.0692        | 24.0  | 672  | 1.7622          | 0.6585   |
| 0.1092        | 25.0  | 700  | 2.0505          | 0.6585   |
| 0.0584        | 26.0  | 728  | 2.2675          | 0.5610   |
| 0.0661        | 27.0  | 756  | 1.7051          | 0.7073   |
| 0.0353        | 28.0  | 784  | 1.9468          | 0.6585   |
| 0.0164        | 29.0  | 812  | 2.4092          | 0.6341   |
| 0.0019        | 30.0  | 840  | 2.7744          | 0.6585   |
| 0.0033        | 31.0  | 868  | 3.2900          | 0.5610   |
| 0.0105        | 32.0  | 896  | 2.4900          | 0.5854   |
| 0.0008        | 33.0  | 924  | 2.5105          | 0.6341   |
| 0.0047        | 34.0  | 952  | 2.0758          | 0.7073   |
| 0.0004        | 35.0  | 980  | 2.7140          | 0.6585   |
| 0.0           | 36.0  | 1008 | 2.9025          | 0.6585   |
| 0.0013        | 37.0  | 1036 | 2.6654          | 0.6585   |
| 0.0           | 38.0  | 1064 | 2.6558          | 0.6829   |
| 0.0           | 39.0  | 1092 | 2.6667          | 0.6585   |
| 0.0           | 40.0  | 1120 | 2.6779          | 0.6585   |
| 0.0           | 41.0  | 1148 | 2.6850          | 0.6585   |
| 0.0           | 42.0  | 1176 | 2.6917          | 0.6585   |
| 0.0           | 43.0  | 1204 | 2.6986          | 0.6585   |
| 0.0           | 44.0  | 1232 | 2.7032          | 0.6585   |
| 0.0           | 45.0  | 1260 | 2.7065          | 0.6585   |
| 0.0           | 46.0  | 1288 | 2.7090          | 0.6585   |
| 0.0           | 47.0  | 1316 | 2.7107          | 0.6585   |
| 0.0           | 48.0  | 1344 | 2.7115          | 0.6585   |
| 0.0           | 49.0  | 1372 | 2.7115          | 0.6585   |
| 0.0           | 50.0  | 1400 | 2.7115          | 0.6585   |


### 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_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6585365853658537, "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