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# SMIDS_10x_deit_base_rmsprop_lr001_fold3

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6132
- Accuracy: 0.7933

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8209        | 1.0   | 750   | 0.8123          | 0.5667   |
| 0.7845        | 2.0   | 1500  | 0.8203          | 0.6167   |
| 0.6724        | 3.0   | 2250  | 0.7415          | 0.6183   |
| 0.5861        | 4.0   | 3000  | 0.6715          | 0.7      |
| 0.609         | 5.0   | 3750  | 0.6037          | 0.7033   |
| 0.5831        | 6.0   | 4500  | 0.6546          | 0.7233   |
| 0.6105        | 7.0   | 5250  | 0.5827          | 0.7233   |
| 0.5711        | 8.0   | 6000  | 0.5717          | 0.7583   |
| 0.4993        | 9.0   | 6750  | 0.5957          | 0.7583   |
| 0.4948        | 10.0  | 7500  | 0.5652          | 0.7683   |
| 0.5279        | 11.0  | 8250  | 0.5146          | 0.7783   |
| 0.4656        | 12.0  | 9000  | 0.5540          | 0.7583   |
| 0.473         | 13.0  | 9750  | 0.5413          | 0.765    |
| 0.5079        | 14.0  | 10500 | 0.5464          | 0.775    |
| 0.4938        | 15.0  | 11250 | 0.5230          | 0.795    |
| 0.4946        | 16.0  | 12000 | 0.5053          | 0.8      |
| 0.4169        | 17.0  | 12750 | 0.5450          | 0.7633   |
| 0.4706        | 18.0  | 13500 | 0.5201          | 0.7833   |
| 0.4545        | 19.0  | 14250 | 0.5277          | 0.7883   |
| 0.4291        | 20.0  | 15000 | 0.5449          | 0.7917   |
| 0.4001        | 21.0  | 15750 | 0.5382          | 0.79     |
| 0.4168        | 22.0  | 16500 | 0.5195          | 0.8      |
| 0.3935        | 23.0  | 17250 | 0.4896          | 0.7983   |
| 0.4642        | 24.0  | 18000 | 0.4983          | 0.7967   |
| 0.4026        | 25.0  | 18750 | 0.5735          | 0.775    |
| 0.3843        | 26.0  | 19500 | 0.5030          | 0.7883   |
| 0.2832        | 27.0  | 20250 | 0.5181          | 0.81     |
| 0.3424        | 28.0  | 21000 | 0.5840          | 0.805    |
| 0.3324        | 29.0  | 21750 | 0.5751          | 0.8083   |
| 0.2307        | 30.0  | 22500 | 0.6063          | 0.8017   |
| 0.2355        | 31.0  | 23250 | 0.6366          | 0.8      |
| 0.2393        | 32.0  | 24000 | 0.6571          | 0.8017   |
| 0.233         | 33.0  | 24750 | 0.6056          | 0.82     |
| 0.2467        | 34.0  | 25500 | 0.6649          | 0.7717   |
| 0.252         | 35.0  | 26250 | 0.7580          | 0.815    |
| 0.215         | 36.0  | 27000 | 0.7594          | 0.8      |
| 0.1916        | 37.0  | 27750 | 0.8296          | 0.7817   |
| 0.2118        | 38.0  | 28500 | 0.8807          | 0.8033   |
| 0.1959        | 39.0  | 29250 | 0.9203          | 0.8033   |
| 0.1608        | 40.0  | 30000 | 1.0039          | 0.8      |
| 0.1856        | 41.0  | 30750 | 0.9758          | 0.7933   |
| 0.1428        | 42.0  | 31500 | 0.9769          | 0.815    |
| 0.0967        | 43.0  | 32250 | 1.3213          | 0.7933   |
| 0.0908        | 44.0  | 33000 | 1.3631          | 0.79     |
| 0.0609        | 45.0  | 33750 | 1.4257          | 0.7883   |
| 0.0657        | 46.0  | 34500 | 1.6973          | 0.7933   |
| 0.0415        | 47.0  | 35250 | 2.0726          | 0.7883   |
| 0.0161        | 48.0  | 36000 | 2.2307          | 0.7967   |
| 0.0011        | 49.0  | 36750 | 2.5765          | 0.7867   |
| 0.0147        | 50.0  | 37500 | 2.6132          | 0.7933   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-base-patch16-224", "model-index": [{"name": "SMIDS_10x_deit_base_rmsprop_lr001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7933333333333333, "name": "Accuracy"}]}]}]}
transformers safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us