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# smids_3x_deit_tiny_sgd_001_fold1

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: 0.3078
- Accuracy: 0.8731

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9352        | 1.0   | 226   | 0.9208          | 0.5376   |
| 0.6928        | 2.0   | 452   | 0.7389          | 0.6861   |
| 0.5623        | 3.0   | 678   | 0.6105          | 0.7429   |
| 0.5246        | 4.0   | 904   | 0.5485          | 0.7563   |
| 0.5426        | 5.0   | 1130  | 0.4979          | 0.7880   |
| 0.4977        | 6.0   | 1356  | 0.4581          | 0.8080   |
| 0.3766        | 7.0   | 1582  | 0.4327          | 0.8130   |
| 0.4038        | 8.0   | 1808  | 0.4167          | 0.8097   |
| 0.3541        | 9.0   | 2034  | 0.3987          | 0.8431   |
| 0.3195        | 10.0  | 2260  | 0.3857          | 0.8247   |
| 0.3215        | 11.0  | 2486  | 0.3815          | 0.8297   |
| 0.2707        | 12.0  | 2712  | 0.3604          | 0.8414   |
| 0.2756        | 13.0  | 2938  | 0.3575          | 0.8364   |
| 0.2853        | 14.0  | 3164  | 0.3492          | 0.8414   |
| 0.3202        | 15.0  | 3390  | 0.3434          | 0.8447   |
| 0.3213        | 16.0  | 3616  | 0.3398          | 0.8497   |
| 0.246         | 17.0  | 3842  | 0.3305          | 0.8581   |
| 0.2485        | 18.0  | 4068  | 0.3288          | 0.8564   |
| 0.2691        | 19.0  | 4294  | 0.3315          | 0.8598   |
| 0.2123        | 20.0  | 4520  | 0.3213          | 0.8648   |
| 0.2607        | 21.0  | 4746  | 0.3252          | 0.8564   |
| 0.2646        | 22.0  | 4972  | 0.3186          | 0.8664   |
| 0.2851        | 23.0  | 5198  | 0.3202          | 0.8631   |
| 0.2373        | 24.0  | 5424  | 0.3144          | 0.8748   |
| 0.1908        | 25.0  | 5650  | 0.3143          | 0.8698   |
| 0.2924        | 26.0  | 5876  | 0.3120          | 0.8698   |
| 0.1662        | 27.0  | 6102  | 0.3113          | 0.8748   |
| 0.2215        | 28.0  | 6328  | 0.3120          | 0.8681   |
| 0.1838        | 29.0  | 6554  | 0.3136          | 0.8698   |
| 0.2131        | 30.0  | 6780  | 0.3140          | 0.8731   |
| 0.2074        | 31.0  | 7006  | 0.3100          | 0.8715   |
| 0.194         | 32.0  | 7232  | 0.3083          | 0.8748   |
| 0.1635        | 33.0  | 7458  | 0.3091          | 0.8748   |
| 0.1521        | 34.0  | 7684  | 0.3083          | 0.8748   |
| 0.2333        | 35.0  | 7910  | 0.3078          | 0.8748   |
| 0.1942        | 36.0  | 8136  | 0.3076          | 0.8731   |
| 0.242         | 37.0  | 8362  | 0.3062          | 0.8748   |
| 0.2131        | 38.0  | 8588  | 0.3090          | 0.8748   |
| 0.2044        | 39.0  | 8814  | 0.3079          | 0.8748   |
| 0.1565        | 40.0  | 9040  | 0.3082          | 0.8731   |
| 0.1709        | 41.0  | 9266  | 0.3089          | 0.8748   |
| 0.2023        | 42.0  | 9492  | 0.3080          | 0.8748   |
| 0.2299        | 43.0  | 9718  | 0.3077          | 0.8731   |
| 0.1365        | 44.0  | 9944  | 0.3081          | 0.8765   |
| 0.1955        | 45.0  | 10170 | 0.3078          | 0.8748   |
| 0.2025        | 46.0  | 10396 | 0.3089          | 0.8781   |
| 0.1982        | 47.0  | 10622 | 0.3076          | 0.8731   |
| 0.1881        | 48.0  | 10848 | 0.3078          | 0.8731   |
| 0.1389        | 49.0  | 11074 | 0.3077          | 0.8731   |
| 0.1646        | 50.0  | 11300 | 0.3078          | 0.8731   |


### 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": "smids_3x_deit_tiny_sgd_001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8731218697829716, "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