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# hushem_40x_deit_tiny_rms_001_fold4

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: 3.6233
- Accuracy: 0.6905

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1473        | 1.0   | 219   | 0.8756          | 0.6190   |
| 0.9719        | 2.0   | 438   | 0.9893          | 0.5714   |
| 0.7611        | 3.0   | 657   | 0.7217          | 0.7619   |
| 0.6995        | 4.0   | 876   | 0.7516          | 0.6429   |
| 0.6928        | 5.0   | 1095  | 1.0447          | 0.5952   |
| 0.6114        | 6.0   | 1314  | 0.9410          | 0.6667   |
| 0.4906        | 7.0   | 1533  | 1.4457          | 0.5238   |
| 0.4956        | 8.0   | 1752  | 1.1229          | 0.6429   |
| 0.3708        | 9.0   | 1971  | 0.5610          | 0.7381   |
| 0.3213        | 10.0  | 2190  | 1.1632          | 0.6667   |
| 0.279         | 11.0  | 2409  | 0.8853          | 0.7381   |
| 0.26          | 12.0  | 2628  | 1.0316          | 0.6905   |
| 0.2004        | 13.0  | 2847  | 0.8001          | 0.7619   |
| 0.2396        | 14.0  | 3066  | 1.0495          | 0.7381   |
| 0.1937        | 15.0  | 3285  | 1.2736          | 0.7381   |
| 0.1386        | 16.0  | 3504  | 0.9949          | 0.7381   |
| 0.1459        | 17.0  | 3723  | 1.2302          | 0.6905   |
| 0.0754        | 18.0  | 3942  | 1.9238          | 0.6667   |
| 0.0996        | 19.0  | 4161  | 1.4396          | 0.6905   |
| 0.0438        | 20.0  | 4380  | 1.1891          | 0.7143   |
| 0.1349        | 21.0  | 4599  | 1.4228          | 0.7381   |
| 0.0058        | 22.0  | 4818  | 1.2340          | 0.7619   |
| 0.0345        | 23.0  | 5037  | 1.1630          | 0.6667   |
| 0.0461        | 24.0  | 5256  | 2.1318          | 0.6429   |
| 0.0595        | 25.0  | 5475  | 1.7499          | 0.6905   |
| 0.004         | 26.0  | 5694  | 1.6488          | 0.6905   |
| 0.0014        | 27.0  | 5913  | 1.8134          | 0.6905   |
| 0.0335        | 28.0  | 6132  | 2.3351          | 0.6905   |
| 0.0071        | 29.0  | 6351  | 2.4170          | 0.5714   |
| 0.0006        | 30.0  | 6570  | 1.5965          | 0.7381   |
| 0.0014        | 31.0  | 6789  | 2.0937          | 0.7381   |
| 0.0419        | 32.0  | 7008  | 1.8845          | 0.6905   |
| 0.042         | 33.0  | 7227  | 3.6234          | 0.6190   |
| 0.0018        | 34.0  | 7446  | 1.5177          | 0.6905   |
| 0.027         | 35.0  | 7665  | 1.3824          | 0.7857   |
| 0.0005        | 36.0  | 7884  | 2.3915          | 0.7619   |
| 0.0226        | 37.0  | 8103  | 1.6001          | 0.7381   |
| 0.001         | 38.0  | 8322  | 2.3141          | 0.6905   |
| 0.0           | 39.0  | 8541  | 2.5460          | 0.7143   |
| 0.0           | 40.0  | 8760  | 2.6724          | 0.6905   |
| 0.0           | 41.0  | 8979  | 2.7005          | 0.6905   |
| 0.0           | 42.0  | 9198  | 2.8171          | 0.7143   |
| 0.0           | 43.0  | 9417  | 2.9876          | 0.7143   |
| 0.0           | 44.0  | 9636  | 3.1125          | 0.7143   |
| 0.0           | 45.0  | 9855  | 3.2479          | 0.7143   |
| 0.0           | 46.0  | 10074 | 3.4344          | 0.7143   |
| 0.0           | 47.0  | 10293 | 3.4573          | 0.7143   |
| 0.0           | 48.0  | 10512 | 3.5752          | 0.6905   |
| 0.0           | 49.0  | 10731 | 3.5910          | 0.6905   |
| 0.0           | 50.0  | 10950 | 3.6233          | 0.6905   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "hushem_40x_deit_tiny_rms_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": 0.6904761904761905, "name": "Accuracy"}]}]}]}
transformers pytorch 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