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# smids_1x_deit_tiny_adamax_00001_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: 0.7515
- Accuracy: 0.8514

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6291        | 1.0   | 76   | 0.6157          | 0.7212   |
| 0.4871        | 2.0   | 152  | 0.4955          | 0.7663   |
| 0.3563        | 3.0   | 228  | 0.4334          | 0.8147   |
| 0.3532        | 4.0   | 304  | 0.4038          | 0.8264   |
| 0.2556        | 5.0   | 380  | 0.3826          | 0.8364   |
| 0.1832        | 6.0   | 456  | 0.3763          | 0.8314   |
| 0.188         | 7.0   | 532  | 0.3632          | 0.8364   |
| 0.176         | 8.0   | 608  | 0.3509          | 0.8531   |
| 0.1753        | 9.0   | 684  | 0.3927          | 0.8464   |
| 0.094         | 10.0  | 760  | 0.3701          | 0.8614   |
| 0.1113        | 11.0  | 836  | 0.3673          | 0.8598   |
| 0.0773        | 12.0  | 912  | 0.3708          | 0.8531   |
| 0.0733        | 13.0  | 988  | 0.3810          | 0.8464   |
| 0.0524        | 14.0  | 1064 | 0.3916          | 0.8648   |
| 0.0392        | 15.0  | 1140 | 0.4052          | 0.8648   |
| 0.0271        | 16.0  | 1216 | 0.4245          | 0.8614   |
| 0.0255        | 17.0  | 1292 | 0.4381          | 0.8514   |
| 0.0233        | 18.0  | 1368 | 0.4614          | 0.8698   |
| 0.0233        | 19.0  | 1444 | 0.4762          | 0.8614   |
| 0.0102        | 20.0  | 1520 | 0.4954          | 0.8664   |
| 0.0235        | 21.0  | 1596 | 0.5367          | 0.8564   |
| 0.0283        | 22.0  | 1672 | 0.5394          | 0.8681   |
| 0.0037        | 23.0  | 1748 | 0.5607          | 0.8598   |
| 0.0016        | 24.0  | 1824 | 0.5901          | 0.8564   |
| 0.0188        | 25.0  | 1900 | 0.5950          | 0.8564   |
| 0.0156        | 26.0  | 1976 | 0.6264          | 0.8531   |
| 0.0197        | 27.0  | 2052 | 0.6288          | 0.8598   |
| 0.009         | 28.0  | 2128 | 0.6474          | 0.8531   |
| 0.025         | 29.0  | 2204 | 0.6597          | 0.8564   |
| 0.0005        | 30.0  | 2280 | 0.6571          | 0.8548   |
| 0.0131        | 31.0  | 2356 | 0.6711          | 0.8531   |
| 0.0183        | 32.0  | 2432 | 0.6793          | 0.8581   |
| 0.0003        | 33.0  | 2508 | 0.6998          | 0.8514   |
| 0.0004        | 34.0  | 2584 | 0.6868          | 0.8564   |
| 0.0226        | 35.0  | 2660 | 0.7047          | 0.8564   |
| 0.0145        | 36.0  | 2736 | 0.7054          | 0.8548   |
| 0.0171        | 37.0  | 2812 | 0.7259          | 0.8464   |
| 0.0011        | 38.0  | 2888 | 0.7392          | 0.8481   |
| 0.0066        | 39.0  | 2964 | 0.7347          | 0.8481   |
| 0.0002        | 40.0  | 3040 | 0.7257          | 0.8564   |
| 0.0087        | 41.0  | 3116 | 0.7270          | 0.8548   |
| 0.0004        | 42.0  | 3192 | 0.7348          | 0.8631   |
| 0.0075        | 43.0  | 3268 | 0.7382          | 0.8564   |
| 0.0002        | 44.0  | 3344 | 0.7585          | 0.8447   |
| 0.0002        | 45.0  | 3420 | 0.7418          | 0.8531   |
| 0.0002        | 46.0  | 3496 | 0.7509          | 0.8497   |
| 0.0002        | 47.0  | 3572 | 0.7508          | 0.8514   |
| 0.0054        | 48.0  | 3648 | 0.7479          | 0.8514   |
| 0.0002        | 49.0  | 3724 | 0.7520          | 0.8514   |
| 0.0002        | 50.0  | 3800 | 0.7515          | 0.8514   |


### 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-tiny-patch16-224", "model-index": [{"name": "smids_1x_deit_tiny_adamax_00001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8514190317195326, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors 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