
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# smids_1x_deit_tiny_rms_0001_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: 1.2046
- Accuracy: 0.8517

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7851        | 1.0   | 75   | 0.8659          | 0.64     |
| 0.6518        | 2.0   | 150  | 0.7541          | 0.6467   |
| 0.4507        | 3.0   | 225  | 0.6126          | 0.755    |
| 0.4597        | 4.0   | 300  | 0.4698          | 0.805    |
| 0.3528        | 5.0   | 375  | 0.4309          | 0.835    |
| 0.2717        | 6.0   | 450  | 0.4110          | 0.8517   |
| 0.2211        | 7.0   | 525  | 0.5132          | 0.8283   |
| 0.1873        | 8.0   | 600  | 0.5255          | 0.835    |
| 0.1509        | 9.0   | 675  | 0.5409          | 0.85     |
| 0.06          | 10.0  | 750  | 0.7466          | 0.8333   |
| 0.1297        | 11.0  | 825  | 0.8027          | 0.835    |
| 0.0789        | 12.0  | 900  | 0.7518          | 0.8417   |
| 0.1522        | 13.0  | 975  | 0.7901          | 0.8533   |
| 0.0628        | 14.0  | 1050 | 0.8326          | 0.845    |
| 0.0732        | 15.0  | 1125 | 0.9433          | 0.8317   |
| 0.0276        | 16.0  | 1200 | 0.9028          | 0.845    |
| 0.0402        | 17.0  | 1275 | 0.8882          | 0.8617   |
| 0.0561        | 18.0  | 1350 | 0.9516          | 0.8367   |
| 0.0072        | 19.0  | 1425 | 1.0341          | 0.8467   |
| 0.0251        | 20.0  | 1500 | 1.0436          | 0.8433   |
| 0.0171        | 21.0  | 1575 | 0.8887          | 0.855    |
| 0.0141        | 22.0  | 1650 | 0.9265          | 0.8517   |
| 0.0297        | 23.0  | 1725 | 1.1359          | 0.8383   |
| 0.0008        | 24.0  | 1800 | 1.0337          | 0.8567   |
| 0.0322        | 25.0  | 1875 | 0.8913          | 0.87     |
| 0.0416        | 26.0  | 1950 | 0.9175          | 0.84     |
| 0.0268        | 27.0  | 2025 | 0.9551          | 0.86     |
| 0.0237        | 28.0  | 2100 | 1.0150          | 0.8533   |
| 0.0252        | 29.0  | 2175 | 0.8872          | 0.8617   |
| 0.0035        | 30.0  | 2250 | 0.9489          | 0.8633   |
| 0.0155        | 31.0  | 2325 | 1.0473          | 0.8417   |
| 0.0007        | 32.0  | 2400 | 0.9648          | 0.8533   |
| 0.0102        | 33.0  | 2475 | 1.0603          | 0.8517   |
| 0.0           | 34.0  | 2550 | 1.0445          | 0.8533   |
| 0.0057        | 35.0  | 2625 | 1.0369          | 0.8467   |
| 0.0           | 36.0  | 2700 | 1.0577          | 0.8517   |
| 0.004         | 37.0  | 2775 | 1.0782          | 0.845    |
| 0.0033        | 38.0  | 2850 | 1.1658          | 0.8433   |
| 0.0001        | 39.0  | 2925 | 1.0942          | 0.8533   |
| 0.0           | 40.0  | 3000 | 1.1718          | 0.8467   |
| 0.0038        | 41.0  | 3075 | 1.1726          | 0.855    |
| 0.0           | 42.0  | 3150 | 1.1472          | 0.85     |
| 0.008         | 43.0  | 3225 | 1.1850          | 0.8517   |
| 0.0008        | 44.0  | 3300 | 1.1576          | 0.845    |
| 0.0022        | 45.0  | 3375 | 1.1935          | 0.855    |
| 0.0           | 46.0  | 3450 | 1.1973          | 0.8533   |
| 0.0056        | 47.0  | 3525 | 1.2032          | 0.8533   |
| 0.0051        | 48.0  | 3600 | 1.2041          | 0.8533   |
| 0.0           | 49.0  | 3675 | 1.2053          | 0.8517   |
| 0.0043        | 50.0  | 3750 | 1.2046          | 0.8517   |


### 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_rms_0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8516666666666667, "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