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# smids_1x_deit_tiny_adamax_00001_fold3

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: 0.6352
- Accuracy: 0.8933

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7543        | 1.0   | 75   | 0.6805          | 0.7367   |
| 0.4751        | 2.0   | 150  | 0.5095          | 0.8067   |
| 0.4299        | 3.0   | 225  | 0.4326          | 0.83     |
| 0.3631        | 4.0   | 300  | 0.4020          | 0.85     |
| 0.2821        | 5.0   | 375  | 0.3807          | 0.8517   |
| 0.249         | 6.0   | 450  | 0.3472          | 0.8733   |
| 0.2583        | 7.0   | 525  | 0.3378          | 0.8767   |
| 0.1796        | 8.0   | 600  | 0.3350          | 0.88     |
| 0.19          | 9.0   | 675  | 0.3308          | 0.88     |
| 0.1195        | 10.0  | 750  | 0.3410          | 0.8717   |
| 0.1538        | 11.0  | 825  | 0.3347          | 0.8767   |
| 0.1042        | 12.0  | 900  | 0.3292          | 0.895    |
| 0.1212        | 13.0  | 975  | 0.3308          | 0.895    |
| 0.0747        | 14.0  | 1050 | 0.3402          | 0.885    |
| 0.0423        | 15.0  | 1125 | 0.3519          | 0.89     |
| 0.0318        | 16.0  | 1200 | 0.3697          | 0.8867   |
| 0.0388        | 17.0  | 1275 | 0.3821          | 0.8883   |
| 0.0223        | 18.0  | 1350 | 0.3957          | 0.885    |
| 0.0206        | 19.0  | 1425 | 0.4157          | 0.885    |
| 0.0272        | 20.0  | 1500 | 0.4298          | 0.8883   |
| 0.007         | 21.0  | 1575 | 0.4227          | 0.8917   |
| 0.0064        | 22.0  | 1650 | 0.4518          | 0.895    |
| 0.0167        | 23.0  | 1725 | 0.4704          | 0.89     |
| 0.0018        | 24.0  | 1800 | 0.4600          | 0.8867   |
| 0.0144        | 25.0  | 1875 | 0.4875          | 0.89     |
| 0.0149        | 26.0  | 1950 | 0.5302          | 0.8817   |
| 0.0149        | 27.0  | 2025 | 0.5247          | 0.8917   |
| 0.001         | 28.0  | 2100 | 0.5348          | 0.8883   |
| 0.0008        | 29.0  | 2175 | 0.5323          | 0.8883   |
| 0.0008        | 30.0  | 2250 | 0.5459          | 0.89     |
| 0.0005        | 31.0  | 2325 | 0.5595          | 0.8883   |
| 0.0008        | 32.0  | 2400 | 0.5625          | 0.8917   |
| 0.0049        | 33.0  | 2475 | 0.5790          | 0.8867   |
| 0.0102        | 34.0  | 2550 | 0.5778          | 0.89     |
| 0.0263        | 35.0  | 2625 | 0.6019          | 0.89     |
| 0.01          | 36.0  | 2700 | 0.5907          | 0.8883   |
| 0.0005        | 37.0  | 2775 | 0.6086          | 0.8867   |
| 0.0003        | 38.0  | 2850 | 0.6091          | 0.8917   |
| 0.0002        | 39.0  | 2925 | 0.6105          | 0.8883   |
| 0.0002        | 40.0  | 3000 | 0.6065          | 0.8933   |
| 0.0002        | 41.0  | 3075 | 0.6175          | 0.8883   |
| 0.0165        | 42.0  | 3150 | 0.6281          | 0.8917   |
| 0.0088        | 43.0  | 3225 | 0.6246          | 0.8883   |
| 0.0003        | 44.0  | 3300 | 0.6288          | 0.89     |
| 0.0015        | 45.0  | 3375 | 0.6290          | 0.89     |
| 0.0021        | 46.0  | 3450 | 0.6320          | 0.89     |
| 0.0189        | 47.0  | 3525 | 0.6360          | 0.8867   |
| 0.0002        | 48.0  | 3600 | 0.6334          | 0.8933   |
| 0.0003        | 49.0  | 3675 | 0.6347          | 0.8933   |
| 0.0086        | 50.0  | 3750 | 0.6352          | 0.8933   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8933333333333333, "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