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# smids_1x_deit_small_adamax_001_fold1

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: 0.9274
- Accuracy: 0.8781

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7007        | 1.0   | 76   | 0.6595          | 0.7362   |
| 0.4949        | 2.0   | 152  | 0.4467          | 0.8247   |
| 0.3674        | 3.0   | 228  | 0.5673          | 0.7896   |
| 0.3934        | 4.0   | 304  | 0.3697          | 0.8598   |
| 0.2797        | 5.0   | 380  | 0.3646          | 0.8681   |
| 0.1743        | 6.0   | 456  | 0.5610          | 0.8314   |
| 0.205         | 7.0   | 532  | 0.4358          | 0.8514   |
| 0.1774        | 8.0   | 608  | 0.5386          | 0.8297   |
| 0.2157        | 9.0   | 684  | 0.6881          | 0.7863   |
| 0.1067        | 10.0  | 760  | 0.4110          | 0.8798   |
| 0.1404        | 11.0  | 836  | 0.5543          | 0.8514   |
| 0.0545        | 12.0  | 912  | 0.6338          | 0.8464   |
| 0.0886        | 13.0  | 988  | 0.5900          | 0.8531   |
| 0.0855        | 14.0  | 1064 | 0.6471          | 0.8447   |
| 0.0787        | 15.0  | 1140 | 0.5610          | 0.8648   |
| 0.0216        | 16.0  | 1216 | 0.7846          | 0.8664   |
| 0.0158        | 17.0  | 1292 | 0.9724          | 0.8614   |
| 0.0343        | 18.0  | 1368 | 0.8631          | 0.8481   |
| 0.0043        | 19.0  | 1444 | 0.7197          | 0.8765   |
| 0.0087        | 20.0  | 1520 | 0.6941          | 0.8748   |
| 0.0139        | 21.0  | 1596 | 0.8416          | 0.8514   |
| 0.005         | 22.0  | 1672 | 0.7895          | 0.8681   |
| 0.0003        | 23.0  | 1748 | 0.7713          | 0.8731   |
| 0.0251        | 24.0  | 1824 | 0.7771          | 0.8781   |
| 0.0091        | 25.0  | 1900 | 0.8505          | 0.8848   |
| 0.0036        | 26.0  | 1976 | 0.8475          | 0.8798   |
| 0.0054        | 27.0  | 2052 | 0.8606          | 0.8765   |
| 0.0027        | 28.0  | 2128 | 0.8615          | 0.8848   |
| 0.0048        | 29.0  | 2204 | 0.8705          | 0.8831   |
| 0.0           | 30.0  | 2280 | 0.8694          | 0.8798   |
| 0.0044        | 31.0  | 2356 | 0.8749          | 0.8815   |
| 0.0079        | 32.0  | 2432 | 0.8740          | 0.8815   |
| 0.0           | 33.0  | 2508 | 0.8806          | 0.8848   |
| 0.0           | 34.0  | 2584 | 0.8808          | 0.8815   |
| 0.0095        | 35.0  | 2660 | 0.8885          | 0.8831   |
| 0.0037        | 36.0  | 2736 | 0.8930          | 0.8798   |
| 0.0061        | 37.0  | 2812 | 0.9018          | 0.8831   |
| 0.0           | 38.0  | 2888 | 0.9039          | 0.8781   |
| 0.0029        | 39.0  | 2964 | 0.9042          | 0.8831   |
| 0.0           | 40.0  | 3040 | 0.9042          | 0.8781   |
| 0.0026        | 41.0  | 3116 | 0.9094          | 0.8831   |
| 0.0           | 42.0  | 3192 | 0.9098          | 0.8831   |
| 0.0045        | 43.0  | 3268 | 0.9154          | 0.8831   |
| 0.0           | 44.0  | 3344 | 0.9138          | 0.8781   |
| 0.0           | 45.0  | 3420 | 0.9190          | 0.8815   |
| 0.0           | 46.0  | 3496 | 0.9203          | 0.8798   |
| 0.0           | 47.0  | 3572 | 0.9235          | 0.8781   |
| 0.0026        | 48.0  | 3648 | 0.9263          | 0.8815   |
| 0.0           | 49.0  | 3724 | 0.9273          | 0.8781   |
| 0.0           | 50.0  | 3800 | 0.9274          | 0.8781   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8781302170283807, "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