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# hushem_1x_deit_base_adamax_00001_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: 0.6539
- Accuracy: 0.7907

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.3331          | 0.3953   |
| 1.3593        | 2.0   | 12   | 1.2859          | 0.5581   |
| 1.3593        | 3.0   | 18   | 1.2417          | 0.5581   |
| 1.2039        | 4.0   | 24   | 1.1932          | 0.5581   |
| 1.0598        | 5.0   | 30   | 1.1339          | 0.5581   |
| 1.0598        | 6.0   | 36   | 1.0752          | 0.5814   |
| 0.8965        | 7.0   | 42   | 1.0271          | 0.6977   |
| 0.8965        | 8.0   | 48   | 0.9915          | 0.6744   |
| 0.7657        | 9.0   | 54   | 0.9413          | 0.7209   |
| 0.6159        | 10.0  | 60   | 0.8991          | 0.7209   |
| 0.6159        | 11.0  | 66   | 0.8637          | 0.6744   |
| 0.485         | 12.0  | 72   | 0.8373          | 0.6977   |
| 0.485         | 13.0  | 78   | 0.8208          | 0.6977   |
| 0.3863        | 14.0  | 84   | 0.7902          | 0.7442   |
| 0.3144        | 15.0  | 90   | 0.7725          | 0.7907   |
| 0.3144        | 16.0  | 96   | 0.7576          | 0.7907   |
| 0.2438        | 17.0  | 102  | 0.7436          | 0.7907   |
| 0.2438        | 18.0  | 108  | 0.7294          | 0.8140   |
| 0.193         | 19.0  | 114  | 0.7217          | 0.8140   |
| 0.1581        | 20.0  | 120  | 0.7141          | 0.7907   |
| 0.1581        | 21.0  | 126  | 0.6979          | 0.8140   |
| 0.1306        | 22.0  | 132  | 0.6874          | 0.8140   |
| 0.1306        | 23.0  | 138  | 0.6970          | 0.8140   |
| 0.1005        | 24.0  | 144  | 0.6887          | 0.8140   |
| 0.0911        | 25.0  | 150  | 0.6790          | 0.8140   |
| 0.0911        | 26.0  | 156  | 0.6739          | 0.8140   |
| 0.0714        | 27.0  | 162  | 0.6752          | 0.7907   |
| 0.0714        | 28.0  | 168  | 0.6709          | 0.7907   |
| 0.0651        | 29.0  | 174  | 0.6638          | 0.8140   |
| 0.053         | 30.0  | 180  | 0.6587          | 0.7907   |
| 0.053         | 31.0  | 186  | 0.6642          | 0.7907   |
| 0.0459        | 32.0  | 192  | 0.6649          | 0.7907   |
| 0.0459        | 33.0  | 198  | 0.6606          | 0.7907   |
| 0.0416        | 34.0  | 204  | 0.6572          | 0.7907   |
| 0.0382        | 35.0  | 210  | 0.6545          | 0.7907   |
| 0.0382        | 36.0  | 216  | 0.6526          | 0.7907   |
| 0.0358        | 37.0  | 222  | 0.6540          | 0.7907   |
| 0.0358        | 38.0  | 228  | 0.6543          | 0.7907   |
| 0.0336        | 39.0  | 234  | 0.6546          | 0.7907   |
| 0.0331        | 40.0  | 240  | 0.6538          | 0.7907   |
| 0.0331        | 41.0  | 246  | 0.6539          | 0.7907   |
| 0.0325        | 42.0  | 252  | 0.6539          | 0.7907   |
| 0.0325        | 43.0  | 258  | 0.6539          | 0.7907   |
| 0.0333        | 44.0  | 264  | 0.6539          | 0.7907   |
| 0.0317        | 45.0  | 270  | 0.6539          | 0.7907   |
| 0.0317        | 46.0  | 276  | 0.6539          | 0.7907   |
| 0.0319        | 47.0  | 282  | 0.6539          | 0.7907   |
| 0.0319        | 48.0  | 288  | 0.6539          | 0.7907   |
| 0.033         | 49.0  | 294  | 0.6539          | 0.7907   |
| 0.0315        | 50.0  | 300  | 0.6539          | 0.7907   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- 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_adamax_00001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7906976744186046, "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