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# smids_1x_deit_tiny_rms_00001_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: 1.2549
- Accuracy: 0.8583

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4697        | 1.0   | 75   | 0.4183          | 0.8233   |
| 0.3312        | 2.0   | 150  | 0.3681          | 0.8533   |
| 0.2321        | 3.0   | 225  | 0.4033          | 0.8517   |
| 0.1334        | 4.0   | 300  | 0.3968          | 0.8617   |
| 0.1233        | 5.0   | 375  | 0.4520          | 0.8567   |
| 0.0584        | 6.0   | 450  | 0.5293          | 0.8467   |
| 0.0835        | 7.0   | 525  | 0.5619          | 0.8533   |
| 0.0113        | 8.0   | 600  | 0.7080          | 0.8483   |
| 0.0326        | 9.0   | 675  | 0.7194          | 0.86     |
| 0.0108        | 10.0  | 750  | 0.7779          | 0.8583   |
| 0.0133        | 11.0  | 825  | 0.7881          | 0.8617   |
| 0.0052        | 12.0  | 900  | 0.8341          | 0.87     |
| 0.0272        | 13.0  | 975  | 0.8910          | 0.8617   |
| 0.0077        | 14.0  | 1050 | 0.9561          | 0.8433   |
| 0.0002        | 15.0  | 1125 | 0.9039          | 0.8617   |
| 0.0001        | 16.0  | 1200 | 0.9956          | 0.86     |
| 0.032         | 17.0  | 1275 | 0.9953          | 0.8667   |
| 0.018         | 18.0  | 1350 | 0.9816          | 0.8633   |
| 0.0282        | 19.0  | 1425 | 1.1776          | 0.8467   |
| 0.0002        | 20.0  | 1500 | 1.0796          | 0.8583   |
| 0.0001        | 21.0  | 1575 | 1.1308          | 0.8567   |
| 0.0001        | 22.0  | 1650 | 1.1869          | 0.8467   |
| 0.0001        | 23.0  | 1725 | 1.1953          | 0.86     |
| 0.0134        | 24.0  | 1800 | 1.1511          | 0.85     |
| 0.0197        | 25.0  | 1875 | 1.2279          | 0.8517   |
| 0.0           | 26.0  | 1950 | 1.2715          | 0.8483   |
| 0.0011        | 27.0  | 2025 | 1.2389          | 0.85     |
| 0.0034        | 28.0  | 2100 | 1.2470          | 0.85     |
| 0.0076        | 29.0  | 2175 | 1.1531          | 0.8617   |
| 0.0           | 30.0  | 2250 | 1.2325          | 0.85     |
| 0.0           | 31.0  | 2325 | 1.2009          | 0.8633   |
| 0.0           | 32.0  | 2400 | 1.2311          | 0.85     |
| 0.0           | 33.0  | 2475 | 1.2487          | 0.8583   |
| 0.0           | 34.0  | 2550 | 1.2363          | 0.8567   |
| 0.0           | 35.0  | 2625 | 1.2306          | 0.8567   |
| 0.0           | 36.0  | 2700 | 1.2366          | 0.86     |
| 0.0048        | 37.0  | 2775 | 1.2202          | 0.8567   |
| 0.0           | 38.0  | 2850 | 1.2263          | 0.86     |
| 0.0           | 39.0  | 2925 | 1.2319          | 0.8617   |
| 0.0           | 40.0  | 3000 | 1.2616          | 0.8533   |
| 0.0038        | 41.0  | 3075 | 1.2358          | 0.8583   |
| 0.0           | 42.0  | 3150 | 1.2473          | 0.8583   |
| 0.0           | 43.0  | 3225 | 1.2419          | 0.8567   |
| 0.0           | 44.0  | 3300 | 1.2543          | 0.8583   |
| 0.0           | 45.0  | 3375 | 1.2531          | 0.8567   |
| 0.0           | 46.0  | 3450 | 1.2531          | 0.8583   |
| 0.0           | 47.0  | 3525 | 1.2531          | 0.8583   |
| 0.0           | 48.0  | 3600 | 1.2543          | 0.8583   |
| 0.0           | 49.0  | 3675 | 1.2544          | 0.8583   |
| 0.0           | 50.0  | 3750 | 1.2549          | 0.8583   |


### 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_rms_00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8583333333333333, "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