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# hushem_5x_beit_base_adamax_00001_fold1

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3063
- Accuracy: 0.6889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2914        | 1.0   | 27   | 1.3981          | 0.3111   |
| 0.7752        | 2.0   | 54   | 1.2587          | 0.4222   |
| 0.473         | 3.0   | 81   | 1.1213          | 0.6      |
| 0.3517        | 4.0   | 108  | 1.0654          | 0.5778   |
| 0.2036        | 5.0   | 135  | 0.9700          | 0.6222   |
| 0.1396        | 6.0   | 162  | 0.9127          | 0.6444   |
| 0.1055        | 7.0   | 189  | 1.0554          | 0.6222   |
| 0.0683        | 8.0   | 216  | 0.9132          | 0.6222   |
| 0.0509        | 9.0   | 243  | 1.0907          | 0.6222   |
| 0.0285        | 10.0  | 270  | 1.0220          | 0.6667   |
| 0.0302        | 11.0  | 297  | 0.9814          | 0.6667   |
| 0.0178        | 12.0  | 324  | 1.0288          | 0.6667   |
| 0.0215        | 13.0  | 351  | 0.9906          | 0.6667   |
| 0.0098        | 14.0  | 378  | 0.9906          | 0.6667   |
| 0.0094        | 15.0  | 405  | 0.9909          | 0.6667   |
| 0.0079        | 16.0  | 432  | 1.0583          | 0.6889   |
| 0.0176        | 17.0  | 459  | 1.0002          | 0.7111   |
| 0.0071        | 18.0  | 486  | 1.1076          | 0.7111   |
| 0.0077        | 19.0  | 513  | 1.2658          | 0.7111   |
| 0.0085        | 20.0  | 540  | 1.2202          | 0.7111   |
| 0.0042        | 21.0  | 567  | 1.1485          | 0.6889   |
| 0.0109        | 22.0  | 594  | 1.1833          | 0.6667   |
| 0.0017        | 23.0  | 621  | 1.2496          | 0.6667   |
| 0.0025        | 24.0  | 648  | 1.2268          | 0.6667   |
| 0.0049        | 25.0  | 675  | 1.1304          | 0.6889   |
| 0.0023        | 26.0  | 702  | 1.0752          | 0.6667   |
| 0.002         | 27.0  | 729  | 1.3029          | 0.6889   |
| 0.0019        | 28.0  | 756  | 1.1867          | 0.6444   |
| 0.0014        | 29.0  | 783  | 1.1802          | 0.7333   |
| 0.002         | 30.0  | 810  | 1.3660          | 0.7111   |
| 0.0126        | 31.0  | 837  | 1.3022          | 0.6889   |
| 0.002         | 32.0  | 864  | 1.3902          | 0.6667   |
| 0.0046        | 33.0  | 891  | 1.3937          | 0.6889   |
| 0.0019        | 34.0  | 918  | 1.3856          | 0.7333   |
| 0.0048        | 35.0  | 945  | 1.3752          | 0.6667   |
| 0.002         | 36.0  | 972  | 1.3963          | 0.6667   |
| 0.0009        | 37.0  | 999  | 1.3895          | 0.7111   |
| 0.001         | 38.0  | 1026 | 1.2536          | 0.6889   |
| 0.0016        | 39.0  | 1053 | 1.2991          | 0.6667   |
| 0.0008        | 40.0  | 1080 | 1.2492          | 0.6889   |
| 0.0031        | 41.0  | 1107 | 1.2808          | 0.6889   |
| 0.0025        | 42.0  | 1134 | 1.3015          | 0.6667   |
| 0.0032        | 43.0  | 1161 | 1.3785          | 0.7111   |
| 0.0006        | 44.0  | 1188 | 1.3466          | 0.6889   |
| 0.004         | 45.0  | 1215 | 1.3569          | 0.6667   |
| 0.0022        | 46.0  | 1242 | 1.3406          | 0.6444   |
| 0.0027        | 47.0  | 1269 | 1.3081          | 0.6889   |
| 0.0015        | 48.0  | 1296 | 1.3063          | 0.6889   |
| 0.002         | 49.0  | 1323 | 1.3063          | 0.6889   |
| 0.003         | 50.0  | 1350 | 1.3063          | 0.6889   |


### 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": "microsoft/beit-base-patch16-224", "model-index": [{"name": "hushem_5x_beit_base_adamax_00001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6888888888888889, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us