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# hushem_1x_deit_base_rms_0001_fold3

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5728
- Accuracy: 0.5116

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.5927          | 0.2558   |
| 1.8022        | 2.0   | 12   | 1.4288          | 0.2558   |
| 1.8022        | 3.0   | 18   | 1.5308          | 0.2558   |
| 1.5239        | 4.0   | 24   | 1.4740          | 0.2558   |
| 1.4801        | 5.0   | 30   | 2.2308          | 0.2558   |
| 1.4801        | 6.0   | 36   | 1.4153          | 0.2558   |
| 1.5953        | 7.0   | 42   | 1.4884          | 0.2326   |
| 1.5953        | 8.0   | 48   | 1.5775          | 0.2558   |
| 1.4262        | 9.0   | 54   | 1.4549          | 0.2558   |
| 1.4607        | 10.0  | 60   | 1.4401          | 0.2558   |
| 1.4607        | 11.0  | 66   | 1.3707          | 0.3256   |
| 1.3771        | 12.0  | 72   | 1.3285          | 0.3721   |
| 1.3771        | 13.0  | 78   | 1.2980          | 0.3721   |
| 1.2887        | 14.0  | 84   | 1.6464          | 0.2558   |
| 1.194         | 15.0  | 90   | 1.4572          | 0.2791   |
| 1.194         | 16.0  | 96   | 1.5171          | 0.3256   |
| 1.2311        | 17.0  | 102  | 1.4178          | 0.4186   |
| 1.2311        | 18.0  | 108  | 1.3427          | 0.3256   |
| 1.2234        | 19.0  | 114  | 1.3369          | 0.3721   |
| 1.1384        | 20.0  | 120  | 1.4187          | 0.3721   |
| 1.1384        | 21.0  | 126  | 1.5195          | 0.2558   |
| 1.0551        | 22.0  | 132  | 1.5010          | 0.3488   |
| 1.0551        | 23.0  | 138  | 1.4046          | 0.3721   |
| 0.958         | 24.0  | 144  | 1.2991          | 0.3721   |
| 0.9405        | 25.0  | 150  | 1.3687          | 0.4651   |
| 0.9405        | 26.0  | 156  | 1.8052          | 0.3256   |
| 0.7255        | 27.0  | 162  | 1.6391          | 0.4419   |
| 0.7255        | 28.0  | 168  | 1.3419          | 0.5116   |
| 0.6435        | 29.0  | 174  | 1.7678          | 0.4419   |
| 0.4939        | 30.0  | 180  | 2.2022          | 0.3256   |
| 0.4939        | 31.0  | 186  | 1.6603          | 0.5116   |
| 0.4434        | 32.0  | 192  | 1.5952          | 0.4884   |
| 0.4434        | 33.0  | 198  | 1.7642          | 0.5116   |
| 0.2864        | 34.0  | 204  | 2.0069          | 0.4651   |
| 0.1858        | 35.0  | 210  | 2.5370          | 0.4884   |
| 0.1858        | 36.0  | 216  | 2.2076          | 0.4651   |
| 0.1248        | 37.0  | 222  | 2.7233          | 0.5581   |
| 0.1248        | 38.0  | 228  | 2.6548          | 0.5349   |
| 0.0495        | 39.0  | 234  | 2.4864          | 0.5116   |
| 0.0526        | 40.0  | 240  | 2.5601          | 0.5116   |
| 0.0526        | 41.0  | 246  | 2.5731          | 0.5116   |
| 0.0219        | 42.0  | 252  | 2.5728          | 0.5116   |
| 0.0219        | 43.0  | 258  | 2.5728          | 0.5116   |
| 0.0327        | 44.0  | 264  | 2.5728          | 0.5116   |
| 0.0324        | 45.0  | 270  | 2.5728          | 0.5116   |
| 0.0324        | 46.0  | 276  | 2.5728          | 0.5116   |
| 0.0326        | 47.0  | 282  | 2.5728          | 0.5116   |
| 0.0326        | 48.0  | 288  | 2.5728          | 0.5116   |
| 0.0208        | 49.0  | 294  | 2.5728          | 0.5116   |
| 0.0503        | 50.0  | 300  | 2.5728          | 0.5116   |


### 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-base-patch16-224", "model-index": [{"name": "hushem_1x_deit_base_rms_0001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5116279069767442, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us