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# hushem_1x_deit_base_adamax_001_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: 1.8177
- Accuracy: 0.6279

## 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: 0.001
- 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    | 1.4213          | 0.2558   |
| 1.6944        | 2.0   | 12   | 1.4223          | 0.2558   |
| 1.6944        | 3.0   | 18   | 1.4356          | 0.2558   |
| 1.4104        | 4.0   | 24   | 1.3899          | 0.2558   |
| 1.4138        | 5.0   | 30   | 1.3790          | 0.2558   |
| 1.4138        | 6.0   | 36   | 1.3481          | 0.2558   |
| 1.38          | 7.0   | 42   | 1.3370          | 0.4419   |
| 1.38          | 8.0   | 48   | 1.1768          | 0.4884   |
| 1.2875        | 9.0   | 54   | 1.4426          | 0.2558   |
| 1.3451        | 10.0  | 60   | 1.3489          | 0.3721   |
| 1.3451        | 11.0  | 66   | 1.4974          | 0.0930   |
| 1.358         | 12.0  | 72   | 1.1260          | 0.4884   |
| 1.358         | 13.0  | 78   | 1.2091          | 0.2558   |
| 1.2345        | 14.0  | 84   | 1.4654          | 0.3023   |
| 1.2591        | 15.0  | 90   | 1.2058          | 0.4419   |
| 1.2591        | 16.0  | 96   | 1.2441          | 0.4419   |
| 1.1691        | 17.0  | 102  | 1.5475          | 0.3721   |
| 1.1691        | 18.0  | 108  | 1.1410          | 0.4186   |
| 1.106         | 19.0  | 114  | 1.3744          | 0.4651   |
| 1.0155        | 20.0  | 120  | 1.0730          | 0.5349   |
| 1.0155        | 21.0  | 126  | 1.1330          | 0.4884   |
| 0.8578        | 22.0  | 132  | 0.8490          | 0.6512   |
| 0.8578        | 23.0  | 138  | 1.2329          | 0.5581   |
| 0.8221        | 24.0  | 144  | 0.8247          | 0.6047   |
| 0.8029        | 25.0  | 150  | 0.8615          | 0.7209   |
| 0.8029        | 26.0  | 156  | 1.4388          | 0.4651   |
| 0.8866        | 27.0  | 162  | 0.9162          | 0.5814   |
| 0.8866        | 28.0  | 168  | 0.9617          | 0.6512   |
| 0.7595        | 29.0  | 174  | 0.8582          | 0.6279   |
| 0.6117        | 30.0  | 180  | 1.0142          | 0.6512   |
| 0.6117        | 31.0  | 186  | 1.2731          | 0.6512   |
| 0.6007        | 32.0  | 192  | 1.1454          | 0.6279   |
| 0.6007        | 33.0  | 198  | 0.9205          | 0.6744   |
| 0.5463        | 34.0  | 204  | 1.2293          | 0.6744   |
| 0.4378        | 35.0  | 210  | 1.3367          | 0.6512   |
| 0.4378        | 36.0  | 216  | 1.0885          | 0.6512   |
| 0.4154        | 37.0  | 222  | 1.7651          | 0.6744   |
| 0.4154        | 38.0  | 228  | 1.3160          | 0.5814   |
| 0.3817        | 39.0  | 234  | 2.0046          | 0.6279   |
| 0.3462        | 40.0  | 240  | 1.4912          | 0.6279   |
| 0.3462        | 41.0  | 246  | 1.7923          | 0.6047   |
| 0.3206        | 42.0  | 252  | 1.8177          | 0.6279   |
| 0.3206        | 43.0  | 258  | 1.8177          | 0.6279   |
| 0.3043        | 44.0  | 264  | 1.8177          | 0.6279   |
| 0.2864        | 45.0  | 270  | 1.8177          | 0.6279   |
| 0.2864        | 46.0  | 276  | 1.8177          | 0.6279   |
| 0.3222        | 47.0  | 282  | 1.8177          | 0.6279   |
| 0.3222        | 48.0  | 288  | 1.8177          | 0.6279   |
| 0.3546        | 49.0  | 294  | 1.8177          | 0.6279   |
| 0.3175        | 50.0  | 300  | 1.8177          | 0.6279   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1

{"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_adamax_001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.627906976744186, "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