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# hushem_5x_deit_base_adamax_001_fold1

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: 5.3716
- Accuracy: 0.4444

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4051        | 1.0   | 27   | 1.4119          | 0.2667   |
| 1.4631        | 2.0   | 54   | 1.4906          | 0.2444   |
| 1.1049        | 3.0   | 81   | 1.5988          | 0.2889   |
| 1.1893        | 4.0   | 108  | 1.5499          | 0.3778   |
| 0.8095        | 5.0   | 135  | 1.4187          | 0.3778   |
| 0.7867        | 6.0   | 162  | 1.5747          | 0.4444   |
| 0.8062        | 7.0   | 189  | 1.7621          | 0.3778   |
| 0.6185        | 8.0   | 216  | 1.6443          | 0.3778   |
| 0.6622        | 9.0   | 243  | 2.0501          | 0.4      |
| 0.7761        | 10.0  | 270  | 1.5776          | 0.3778   |
| 0.7478        | 11.0  | 297  | 1.4437          | 0.3556   |
| 0.6339        | 12.0  | 324  | 1.4821          | 0.4      |
| 0.6965        | 13.0  | 351  | 1.6662          | 0.3556   |
| 0.5829        | 14.0  | 378  | 1.5844          | 0.3778   |
| 0.4908        | 15.0  | 405  | 2.2476          | 0.3778   |
| 0.5234        | 16.0  | 432  | 1.3445          | 0.4222   |
| 0.4872        | 17.0  | 459  | 2.4054          | 0.3556   |
| 0.466         | 18.0  | 486  | 1.6395          | 0.4      |
| 0.4427        | 19.0  | 513  | 1.8006          | 0.4      |
| 0.3436        | 20.0  | 540  | 1.6496          | 0.4      |
| 0.3213        | 21.0  | 567  | 2.4490          | 0.3778   |
| 0.3024        | 22.0  | 594  | 1.9317          | 0.4222   |
| 0.3831        | 23.0  | 621  | 2.1520          | 0.3556   |
| 0.2575        | 24.0  | 648  | 2.1832          | 0.4      |
| 0.3022        | 25.0  | 675  | 2.7719          | 0.4222   |
| 0.2889        | 26.0  | 702  | 2.2904          | 0.3778   |
| 0.1794        | 27.0  | 729  | 2.3541          | 0.3778   |
| 0.1256        | 28.0  | 756  | 3.3430          | 0.4444   |
| 0.1586        | 29.0  | 783  | 2.5549          | 0.4      |
| 0.1387        | 30.0  | 810  | 2.5659          | 0.3778   |
| 0.0828        | 31.0  | 837  | 3.1241          | 0.4      |
| 0.0717        | 32.0  | 864  | 3.9424          | 0.4222   |
| 0.0424        | 33.0  | 891  | 4.2735          | 0.4444   |
| 0.0451        | 34.0  | 918  | 4.8532          | 0.4222   |
| 0.0483        | 35.0  | 945  | 5.1314          | 0.4444   |
| 0.0395        | 36.0  | 972  | 4.8009          | 0.4      |
| 0.0349        | 37.0  | 999  | 4.7979          | 0.4222   |
| 0.003         | 38.0  | 1026 | 5.0139          | 0.4222   |
| 0.0007        | 39.0  | 1053 | 5.1670          | 0.4222   |
| 0.0004        | 40.0  | 1080 | 5.3634          | 0.4444   |
| 0.0028        | 41.0  | 1107 | 5.3467          | 0.4667   |
| 0.0002        | 42.0  | 1134 | 5.3534          | 0.4667   |
| 0.0001        | 43.0  | 1161 | 5.3434          | 0.4667   |
| 0.0001        | 44.0  | 1188 | 5.3497          | 0.4444   |
| 0.0001        | 45.0  | 1215 | 5.3599          | 0.4444   |
| 0.0001        | 46.0  | 1242 | 5.3641          | 0.4444   |
| 0.0001        | 47.0  | 1269 | 5.3694          | 0.4444   |
| 0.0001        | 48.0  | 1296 | 5.3716          | 0.4444   |
| 0.0001        | 49.0  | 1323 | 5.3716          | 0.4444   |
| 0.0001        | 50.0  | 1350 | 5.3716          | 0.4444   |


### 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_5x_deit_base_adamax_001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.4444444444444444, "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