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# smids_1x_deit_small_adamax_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: 0.9149
- Accuracy: 0.8802

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.543         | 1.0   | 75   | 0.5577          | 0.7404   |
| 0.4238        | 2.0   | 150  | 0.4831          | 0.8120   |
| 0.4445        | 3.0   | 225  | 0.4591          | 0.8270   |
| 0.3847        | 4.0   | 300  | 0.4713          | 0.8369   |
| 0.2952        | 5.0   | 375  | 0.3692          | 0.8469   |
| 0.2663        | 6.0   | 450  | 0.4477          | 0.8336   |
| 0.2425        | 7.0   | 525  | 0.4906          | 0.8502   |
| 0.1718        | 8.0   | 600  | 0.4129          | 0.8486   |
| 0.181         | 9.0   | 675  | 0.4664          | 0.8369   |
| 0.1507        | 10.0  | 750  | 0.5087          | 0.8586   |
| 0.054         | 11.0  | 825  | 0.5852          | 0.8586   |
| 0.0682        | 12.0  | 900  | 0.4416          | 0.8669   |
| 0.0775        | 13.0  | 975  | 0.5468          | 0.8519   |
| 0.055         | 14.0  | 1050 | 0.7735          | 0.8469   |
| 0.1251        | 15.0  | 1125 | 0.6731          | 0.8453   |
| 0.0456        | 16.0  | 1200 | 0.6293          | 0.8586   |
| 0.0062        | 17.0  | 1275 | 0.8660          | 0.8502   |
| 0.098         | 18.0  | 1350 | 0.7112          | 0.8502   |
| 0.0187        | 19.0  | 1425 | 0.7932          | 0.8602   |
| 0.0128        | 20.0  | 1500 | 0.8437          | 0.8519   |
| 0.0006        | 21.0  | 1575 | 0.9421          | 0.8686   |
| 0.0053        | 22.0  | 1650 | 0.7611          | 0.8735   |
| 0.0134        | 23.0  | 1725 | 0.8550          | 0.8735   |
| 0.0005        | 24.0  | 1800 | 0.9144          | 0.8835   |
| 0.0024        | 25.0  | 1875 | 0.8153          | 0.8719   |
| 0.0042        | 26.0  | 1950 | 0.9985          | 0.8636   |
| 0.004         | 27.0  | 2025 | 0.9075          | 0.8735   |
| 0.0044        | 28.0  | 2100 | 0.8893          | 0.8735   |
| 0.0063        | 29.0  | 2175 | 0.8699          | 0.8802   |
| 0.0032        | 30.0  | 2250 | 0.8845          | 0.8719   |
| 0.0061        | 31.0  | 2325 | 0.8727          | 0.8785   |
| 0.0           | 32.0  | 2400 | 0.9476          | 0.8702   |
| 0.0001        | 33.0  | 2475 | 0.9392          | 0.8686   |
| 0.0295        | 34.0  | 2550 | 0.8832          | 0.8702   |
| 0.0089        | 35.0  | 2625 | 0.9008          | 0.8719   |
| 0.0029        | 36.0  | 2700 | 0.8983          | 0.8785   |
| 0.003         | 37.0  | 2775 | 0.8653          | 0.8752   |
| 0.0001        | 38.0  | 2850 | 0.8770          | 0.8769   |
| 0.0019        | 39.0  | 2925 | 0.8968          | 0.8752   |
| 0.0           | 40.0  | 3000 | 0.9023          | 0.8785   |
| 0.0031        | 41.0  | 3075 | 0.9066          | 0.8785   |
| 0.0001        | 42.0  | 3150 | 0.9074          | 0.8785   |
| 0.0028        | 43.0  | 3225 | 0.9037          | 0.8785   |
| 0.003         | 44.0  | 3300 | 0.9128          | 0.8785   |
| 0.0           | 45.0  | 3375 | 0.9191          | 0.8785   |
| 0.0           | 46.0  | 3450 | 0.9118          | 0.8785   |
| 0.0026        | 47.0  | 3525 | 0.9156          | 0.8785   |
| 0.0           | 48.0  | 3600 | 0.9135          | 0.8785   |
| 0.0023        | 49.0  | 3675 | 0.9151          | 0.8802   |
| 0.0022        | 50.0  | 3750 | 0.9149          | 0.8802   |


### 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_adamax_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": 0.8801996672212978, "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