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# smids_1x_deit_tiny_rms_00001_fold2

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: 0.8725
- Accuracy: 0.8852

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4335        | 1.0   | 75   | 0.3629          | 0.8519   |
| 0.2445        | 2.0   | 150  | 0.3163          | 0.8752   |
| 0.1892        | 3.0   | 225  | 0.3276          | 0.8719   |
| 0.1722        | 4.0   | 300  | 0.3320          | 0.8769   |
| 0.1627        | 5.0   | 375  | 0.4052          | 0.8336   |
| 0.0774        | 6.0   | 450  | 0.4177          | 0.8636   |
| 0.0654        | 7.0   | 525  | 0.4298          | 0.8835   |
| 0.0585        | 8.0   | 600  | 0.5091          | 0.8586   |
| 0.0287        | 9.0   | 675  | 0.5515          | 0.8785   |
| 0.0409        | 10.0  | 750  | 0.6043          | 0.8735   |
| 0.0028        | 11.0  | 825  | 0.6415          | 0.8852   |
| 0.015         | 12.0  | 900  | 0.7011          | 0.8819   |
| 0.0186        | 13.0  | 975  | 0.7682          | 0.8669   |
| 0.0337        | 14.0  | 1050 | 0.7658          | 0.8669   |
| 0.0071        | 15.0  | 1125 | 0.7841          | 0.8636   |
| 0.0427        | 16.0  | 1200 | 0.8228          | 0.8702   |
| 0.0064        | 17.0  | 1275 | 0.8036          | 0.8752   |
| 0.0151        | 18.0  | 1350 | 0.8626          | 0.8719   |
| 0.0002        | 19.0  | 1425 | 0.8177          | 0.8819   |
| 0.0112        | 20.0  | 1500 | 0.8351          | 0.8636   |
| 0.0001        | 21.0  | 1575 | 0.8049          | 0.8869   |
| 0.0032        | 22.0  | 1650 | 0.8268          | 0.8735   |
| 0.0001        | 23.0  | 1725 | 0.8681          | 0.8752   |
| 0.0001        | 24.0  | 1800 | 0.8420          | 0.8686   |
| 0.0           | 25.0  | 1875 | 0.8252          | 0.8686   |
| 0.0001        | 26.0  | 1950 | 0.8504          | 0.8719   |
| 0.0079        | 27.0  | 2025 | 0.8787          | 0.8769   |
| 0.0047        | 28.0  | 2100 | 0.8232          | 0.8769   |
| 0.0019        | 29.0  | 2175 | 0.8813          | 0.8752   |
| 0.0048        | 30.0  | 2250 | 0.8417          | 0.8652   |
| 0.0115        | 31.0  | 2325 | 0.8526          | 0.8702   |
| 0.0           | 32.0  | 2400 | 0.8276          | 0.8835   |
| 0.0001        | 33.0  | 2475 | 0.8214          | 0.8835   |
| 0.0001        | 34.0  | 2550 | 0.8377          | 0.8802   |
| 0.0182        | 35.0  | 2625 | 0.8794          | 0.8735   |
| 0.0           | 36.0  | 2700 | 0.8604          | 0.8802   |
| 0.0001        | 37.0  | 2775 | 0.8420          | 0.8802   |
| 0.0           | 38.0  | 2850 | 0.9013          | 0.8802   |
| 0.0008        | 39.0  | 2925 | 0.8537          | 0.8819   |
| 0.0           | 40.0  | 3000 | 0.8672          | 0.8819   |
| 0.0029        | 41.0  | 3075 | 0.8548          | 0.8852   |
| 0.0           | 42.0  | 3150 | 0.8641          | 0.8835   |
| 0.002         | 43.0  | 3225 | 0.8645          | 0.8835   |
| 0.0052        | 44.0  | 3300 | 0.8649          | 0.8835   |
| 0.0           | 45.0  | 3375 | 0.8672          | 0.8835   |
| 0.0           | 46.0  | 3450 | 0.8698          | 0.8852   |
| 0.0018        | 47.0  | 3525 | 0.8729          | 0.8852   |
| 0.0           | 48.0  | 3600 | 0.8731          | 0.8852   |
| 0.0032        | 49.0  | 3675 | 0.8719          | 0.8852   |
| 0.0011        | 50.0  | 3750 | 0.8725          | 0.8852   |


### 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_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8851913477537438, "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