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# smids_1x_deit_small_rms_0001_fold5

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: 1.2122
- Accuracy: 0.7483

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0524        | 1.0   | 75   | 0.9597          | 0.445    |
| 1.1247        | 2.0   | 150  | 1.1111          | 0.3367   |
| 0.979         | 3.0   | 225  | 0.9077          | 0.5      |
| 0.8898        | 4.0   | 300  | 0.8740          | 0.52     |
| 0.8714        | 5.0   | 375  | 0.9443          | 0.4433   |
| 0.8755        | 6.0   | 450  | 0.7908          | 0.5917   |
| 0.8257        | 7.0   | 525  | 0.8028          | 0.5817   |
| 0.7602        | 8.0   | 600  | 0.8435          | 0.605    |
| 0.7994        | 9.0   | 675  | 0.7977          | 0.6117   |
| 0.7424        | 10.0  | 750  | 0.7850          | 0.6117   |
| 0.8101        | 11.0  | 825  | 0.7616          | 0.6233   |
| 0.7712        | 12.0  | 900  | 0.7668          | 0.6367   |
| 0.7209        | 13.0  | 975  | 0.8101          | 0.62     |
| 0.7215        | 14.0  | 1050 | 0.7936          | 0.62     |
| 0.7097        | 15.0  | 1125 | 0.7953          | 0.61     |
| 0.7072        | 16.0  | 1200 | 0.7924          | 0.6317   |
| 0.7074        | 17.0  | 1275 | 0.7452          | 0.6667   |
| 0.6856        | 18.0  | 1350 | 0.7477          | 0.6717   |
| 0.6768        | 19.0  | 1425 | 0.7216          | 0.6783   |
| 0.6919        | 20.0  | 1500 | 0.7445          | 0.68     |
| 0.6145        | 21.0  | 1575 | 0.7497          | 0.6533   |
| 0.5852        | 22.0  | 1650 | 0.7462          | 0.7083   |
| 0.625         | 23.0  | 1725 | 0.7496          | 0.675    |
| 0.549         | 24.0  | 1800 | 0.7315          | 0.7067   |
| 0.5773        | 25.0  | 1875 | 0.7055          | 0.7033   |
| 0.5746        | 26.0  | 1950 | 0.6982          | 0.7283   |
| 0.5717        | 27.0  | 2025 | 0.7187          | 0.705    |
| 0.5927        | 28.0  | 2100 | 0.6996          | 0.7183   |
| 0.5713        | 29.0  | 2175 | 0.6989          | 0.7217   |
| 0.5709        | 30.0  | 2250 | 0.7204          | 0.7267   |
| 0.5164        | 31.0  | 2325 | 0.7778          | 0.705    |
| 0.5059        | 32.0  | 2400 | 0.7021          | 0.73     |
| 0.5725        | 33.0  | 2475 | 0.6873          | 0.735    |
| 0.4839        | 34.0  | 2550 | 0.6931          | 0.745    |
| 0.4617        | 35.0  | 2625 | 0.7517          | 0.75     |
| 0.4294        | 36.0  | 2700 | 0.8099          | 0.7533   |
| 0.3749        | 37.0  | 2775 | 0.7255          | 0.75     |
| 0.4163        | 38.0  | 2850 | 0.7476          | 0.7533   |
| 0.3565        | 39.0  | 2925 | 0.8354          | 0.735    |
| 0.382         | 40.0  | 3000 | 0.8201          | 0.7467   |
| 0.3261        | 41.0  | 3075 | 0.8167          | 0.7567   |
| 0.4372        | 42.0  | 3150 | 0.8428          | 0.7267   |
| 0.3484        | 43.0  | 3225 | 0.8996          | 0.74     |
| 0.3261        | 44.0  | 3300 | 0.9207          | 0.735    |
| 0.2963        | 45.0  | 3375 | 1.0220          | 0.7283   |
| 0.2143        | 46.0  | 3450 | 0.9860          | 0.755    |
| 0.2551        | 47.0  | 3525 | 1.1473          | 0.7333   |
| 0.1675        | 48.0  | 3600 | 1.1351          | 0.735    |
| 0.1431        | 49.0  | 3675 | 1.1685          | 0.75     |
| 0.1393        | 50.0  | 3750 | 1.2122          | 0.7483   |


### 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_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": 0.7483333333333333, "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