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# smids_5x_deit_tiny_rms_001_fold4

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: 2.2524
- Accuracy: 0.7767

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.818         | 1.0   | 375   | 0.8019          | 0.5417   |
| 0.7912        | 2.0   | 750   | 0.8025          | 0.57     |
| 0.7276        | 3.0   | 1125  | 0.7672          | 0.6083   |
| 0.7922        | 4.0   | 1500  | 0.6983          | 0.6533   |
| 0.7335        | 5.0   | 1875  | 0.6685          | 0.6917   |
| 0.6959        | 6.0   | 2250  | 0.6471          | 0.7233   |
| 0.623         | 7.0   | 2625  | 0.6073          | 0.7233   |
| 0.6887        | 8.0   | 3000  | 0.6966          | 0.6667   |
| 0.6552        | 9.0   | 3375  | 0.5957          | 0.74     |
| 0.6126        | 10.0  | 3750  | 0.6205          | 0.7      |
| 0.5793        | 11.0  | 4125  | 0.5808          | 0.7567   |
| 0.6219        | 12.0  | 4500  | 0.5874          | 0.745    |
| 0.5436        | 13.0  | 4875  | 0.6140          | 0.7317   |
| 0.6012        | 14.0  | 5250  | 0.5834          | 0.7417   |
| 0.6043        | 15.0  | 5625  | 0.5539          | 0.75     |
| 0.5011        | 16.0  | 6000  | 0.5531          | 0.7383   |
| 0.5057        | 17.0  | 6375  | 0.5890          | 0.75     |
| 0.5517        | 18.0  | 6750  | 0.5510          | 0.7583   |
| 0.5553        | 19.0  | 7125  | 0.5435          | 0.76     |
| 0.5674        | 20.0  | 7500  | 0.4957          | 0.7933   |
| 0.4667        | 21.0  | 7875  | 0.5150          | 0.7867   |
| 0.4405        | 22.0  | 8250  | 0.5576          | 0.7867   |
| 0.4436        | 23.0  | 8625  | 0.4866          | 0.7967   |
| 0.454         | 24.0  | 9000  | 0.5354          | 0.775    |
| 0.4111        | 25.0  | 9375  | 0.5789          | 0.7717   |
| 0.4049        | 26.0  | 9750  | 0.5450          | 0.7817   |
| 0.397         | 27.0  | 10125 | 0.5808          | 0.7883   |
| 0.3436        | 28.0  | 10500 | 0.5933          | 0.7817   |
| 0.3249        | 29.0  | 10875 | 0.5969          | 0.7633   |
| 0.3897        | 30.0  | 11250 | 0.5739          | 0.7817   |
| 0.3938        | 31.0  | 11625 | 0.5794          | 0.7883   |
| 0.2714        | 32.0  | 12000 | 0.6582          | 0.775    |
| 0.2808        | 33.0  | 12375 | 0.6348          | 0.775    |
| 0.321         | 34.0  | 12750 | 0.7200          | 0.7567   |
| 0.2202        | 35.0  | 13125 | 0.6917          | 0.7817   |
| 0.1634        | 36.0  | 13500 | 0.7700          | 0.7733   |
| 0.3232        | 37.0  | 13875 | 0.7503          | 0.785    |
| 0.1845        | 38.0  | 14250 | 0.8724          | 0.7567   |
| 0.1357        | 39.0  | 14625 | 1.0521          | 0.7683   |
| 0.0994        | 40.0  | 15000 | 1.0716          | 0.77     |
| 0.0743        | 41.0  | 15375 | 1.1704          | 0.7717   |
| 0.1059        | 42.0  | 15750 | 1.2031          | 0.7783   |
| 0.0494        | 43.0  | 16125 | 1.3921          | 0.7633   |
| 0.0147        | 44.0  | 16500 | 1.5250          | 0.77     |
| 0.0663        | 45.0  | 16875 | 1.6538          | 0.7667   |
| 0.0618        | 46.0  | 17250 | 1.8210          | 0.765    |
| 0.0041        | 47.0  | 17625 | 1.9243          | 0.7617   |
| 0.0018        | 48.0  | 18000 | 2.1515          | 0.7717   |
| 0.0025        | 49.0  | 18375 | 2.2407          | 0.7683   |
| 0.0002        | 50.0  | 18750 | 2.2524          | 0.7767   |


### 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_5x_deit_tiny_rms_001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7766666666666666, "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