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# smids_1x_deit_tiny_sgd_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: 1.1991
- Accuracy: 0.3667

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3246        | 1.0   | 75   | 1.3568          | 0.3467   |
| 1.3026        | 2.0   | 150  | 1.3478          | 0.3467   |
| 1.3075        | 3.0   | 225  | 1.3392          | 0.3467   |
| 1.3769        | 4.0   | 300  | 1.3310          | 0.3467   |
| 1.2997        | 5.0   | 375  | 1.3231          | 0.3467   |
| 1.2661        | 6.0   | 450  | 1.3158          | 0.3433   |
| 1.2888        | 7.0   | 525  | 1.3087          | 0.3433   |
| 1.2851        | 8.0   | 600  | 1.3020          | 0.3433   |
| 1.2991        | 9.0   | 675  | 1.2955          | 0.3433   |
| 1.3514        | 10.0  | 750  | 1.2893          | 0.345    |
| 1.256         | 11.0  | 825  | 1.2833          | 0.3417   |
| 1.2501        | 12.0  | 900  | 1.2778          | 0.3417   |
| 1.2581        | 13.0  | 975  | 1.2726          | 0.345    |
| 1.279         | 14.0  | 1050 | 1.2675          | 0.345    |
| 1.281         | 15.0  | 1125 | 1.2628          | 0.345    |
| 1.2242        | 16.0  | 1200 | 1.2582          | 0.3483   |
| 1.1785        | 17.0  | 1275 | 1.2539          | 0.3483   |
| 1.2882        | 18.0  | 1350 | 1.2497          | 0.35     |
| 1.2177        | 19.0  | 1425 | 1.2459          | 0.3533   |
| 1.1848        | 20.0  | 1500 | 1.2422          | 0.3567   |
| 1.2931        | 21.0  | 1575 | 1.2388          | 0.3583   |
| 1.2179        | 22.0  | 1650 | 1.2355          | 0.3567   |
| 1.2465        | 23.0  | 1725 | 1.2324          | 0.3567   |
| 1.2403        | 24.0  | 1800 | 1.2294          | 0.355    |
| 1.2116        | 25.0  | 1875 | 1.2267          | 0.355    |
| 1.2221        | 26.0  | 1950 | 1.2242          | 0.36     |
| 1.167         | 27.0  | 2025 | 1.2218          | 0.36     |
| 1.2147        | 28.0  | 2100 | 1.2195          | 0.3583   |
| 1.2367        | 29.0  | 2175 | 1.2174          | 0.355    |
| 1.2142        | 30.0  | 2250 | 1.2154          | 0.355    |
| 1.2312        | 31.0  | 2325 | 1.2136          | 0.3533   |
| 1.1773        | 32.0  | 2400 | 1.2119          | 0.3517   |
| 1.1658        | 33.0  | 2475 | 1.2103          | 0.3517   |
| 1.2038        | 34.0  | 2550 | 1.2088          | 0.355    |
| 1.1521        | 35.0  | 2625 | 1.2075          | 0.3567   |
| 1.1878        | 36.0  | 2700 | 1.2062          | 0.3633   |
| 1.2013        | 37.0  | 2775 | 1.2051          | 0.365    |
| 1.1943        | 38.0  | 2850 | 1.2041          | 0.3633   |
| 1.1839        | 39.0  | 2925 | 1.2032          | 0.3667   |
| 1.1836        | 40.0  | 3000 | 1.2024          | 0.3683   |
| 1.1971        | 41.0  | 3075 | 1.2017          | 0.3683   |
| 1.1901        | 42.0  | 3150 | 1.2011          | 0.365    |
| 1.2156        | 43.0  | 3225 | 1.2005          | 0.365    |
| 1.2062        | 44.0  | 3300 | 1.2001          | 0.365    |
| 1.1956        | 45.0  | 3375 | 1.1998          | 0.365    |
| 1.2469        | 46.0  | 3450 | 1.1995          | 0.3633   |
| 1.1737        | 47.0  | 3525 | 1.1993          | 0.3667   |
| 1.1496        | 48.0  | 3600 | 1.1992          | 0.3667   |
| 1.1899        | 49.0  | 3675 | 1.1991          | 0.3667   |
| 1.2185        | 50.0  | 3750 | 1.1991          | 0.3667   |


### 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_sgd_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": 0.36666666666666664, "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