
<!-- 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_small_sgd_001_fold2

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3804
- Accuracy: 0.8453

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9829        | 1.0   | 75   | 0.9415          | 0.6140   |
| 0.8706        | 2.0   | 150  | 0.8332          | 0.6855   |
| 0.7459        | 3.0   | 225  | 0.7472          | 0.7105   |
| 0.699         | 4.0   | 300  | 0.6837          | 0.7404   |
| 0.6391        | 5.0   | 375  | 0.6363          | 0.7587   |
| 0.5631        | 6.0   | 450  | 0.5989          | 0.7687   |
| 0.5887        | 7.0   | 525  | 0.5694          | 0.7820   |
| 0.5519        | 8.0   | 600  | 0.5464          | 0.7887   |
| 0.4995        | 9.0   | 675  | 0.5237          | 0.7970   |
| 0.5219        | 10.0  | 750  | 0.5075          | 0.8053   |
| 0.4633        | 11.0  | 825  | 0.4946          | 0.8070   |
| 0.4238        | 12.0  | 900  | 0.4804          | 0.8220   |
| 0.4323        | 13.0  | 975  | 0.4699          | 0.8253   |
| 0.358         | 14.0  | 1050 | 0.4601          | 0.8253   |
| 0.3922        | 15.0  | 1125 | 0.4517          | 0.8270   |
| 0.412         | 16.0  | 1200 | 0.4446          | 0.8253   |
| 0.3525        | 17.0  | 1275 | 0.4384          | 0.8236   |
| 0.3851        | 18.0  | 1350 | 0.4333          | 0.8253   |
| 0.4196        | 19.0  | 1425 | 0.4291          | 0.8353   |
| 0.3588        | 20.0  | 1500 | 0.4237          | 0.8286   |
| 0.4139        | 21.0  | 1575 | 0.4192          | 0.8353   |
| 0.3218        | 22.0  | 1650 | 0.4155          | 0.8369   |
| 0.3303        | 23.0  | 1725 | 0.4117          | 0.8419   |
| 0.3481        | 24.0  | 1800 | 0.4077          | 0.8419   |
| 0.3241        | 25.0  | 1875 | 0.4056          | 0.8403   |
| 0.3326        | 26.0  | 1950 | 0.4042          | 0.8453   |
| 0.3492        | 27.0  | 2025 | 0.4005          | 0.8453   |
| 0.2987        | 28.0  | 2100 | 0.3985          | 0.8419   |
| 0.3361        | 29.0  | 2175 | 0.3960          | 0.8453   |
| 0.2986        | 30.0  | 2250 | 0.3933          | 0.8469   |
| 0.2629        | 31.0  | 2325 | 0.3933          | 0.8469   |
| 0.3171        | 32.0  | 2400 | 0.3920          | 0.8453   |
| 0.2746        | 33.0  | 2475 | 0.3904          | 0.8453   |
| 0.2943        | 34.0  | 2550 | 0.3897          | 0.8453   |
| 0.2828        | 35.0  | 2625 | 0.3874          | 0.8453   |
| 0.2865        | 36.0  | 2700 | 0.3865          | 0.8453   |
| 0.2715        | 37.0  | 2775 | 0.3856          | 0.8453   |
| 0.3146        | 38.0  | 2850 | 0.3843          | 0.8453   |
| 0.2703        | 39.0  | 2925 | 0.3840          | 0.8453   |
| 0.2829        | 40.0  | 3000 | 0.3831          | 0.8453   |
| 0.2957        | 41.0  | 3075 | 0.3831          | 0.8453   |
| 0.29          | 42.0  | 3150 | 0.3825          | 0.8469   |
| 0.2671        | 43.0  | 3225 | 0.3820          | 0.8469   |
| 0.262         | 44.0  | 3300 | 0.3814          | 0.8453   |
| 0.2814        | 45.0  | 3375 | 0.3812          | 0.8436   |
| 0.272         | 46.0  | 3450 | 0.3810          | 0.8436   |
| 0.2705        | 47.0  | 3525 | 0.3806          | 0.8453   |
| 0.2571        | 48.0  | 3600 | 0.3805          | 0.8453   |
| 0.267         | 49.0  | 3675 | 0.3804          | 0.8453   |
| 0.2797        | 50.0  | 3750 | 0.3804          | 0.8453   |


### 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-small-patch16-224", "model-index": [{"name": "smids_1x_deit_small_sgd_001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8452579034941764, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us