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# hushem_5x_beit_base_sgd_001_fold2

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: 1.1467
- Accuracy: 0.5111

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4631        | 1.0   | 27   | 1.4879          | 0.2667   |
| 1.4591        | 2.0   | 54   | 1.4319          | 0.2667   |
| 1.4073        | 3.0   | 81   | 1.3901          | 0.2667   |
| 1.3795        | 4.0   | 108  | 1.3753          | 0.2667   |
| 1.2841        | 5.0   | 135  | 1.3518          | 0.2889   |
| 1.2567        | 6.0   | 162  | 1.3273          | 0.3333   |
| 1.2476        | 7.0   | 189  | 1.3161          | 0.3333   |
| 1.2159        | 8.0   | 216  | 1.3027          | 0.3333   |
| 1.1714        | 9.0   | 243  | 1.2935          | 0.3556   |
| 1.1327        | 10.0  | 270  | 1.2804          | 0.4      |
| 1.1283        | 11.0  | 297  | 1.2705          | 0.4      |
| 1.1211        | 12.0  | 324  | 1.2662          | 0.4      |
| 1.085         | 13.0  | 351  | 1.2507          | 0.4      |
| 1.0792        | 14.0  | 378  | 1.2454          | 0.4222   |
| 1.0431        | 15.0  | 405  | 1.2358          | 0.4222   |
| 1.0262        | 16.0  | 432  | 1.2333          | 0.4      |
| 1.0339        | 17.0  | 459  | 1.2202          | 0.4      |
| 1.054         | 18.0  | 486  | 1.2246          | 0.4      |
| 0.9922        | 19.0  | 513  | 1.2085          | 0.4444   |
| 0.9927        | 20.0  | 540  | 1.1996          | 0.4667   |
| 0.9784        | 21.0  | 567  | 1.1934          | 0.4889   |
| 0.9509        | 22.0  | 594  | 1.2003          | 0.4889   |
| 0.8926        | 23.0  | 621  | 1.1949          | 0.4667   |
| 0.9112        | 24.0  | 648  | 1.1944          | 0.4667   |
| 0.9183        | 25.0  | 675  | 1.1878          | 0.4667   |
| 0.922         | 26.0  | 702  | 1.1803          | 0.4889   |
| 0.9154        | 27.0  | 729  | 1.1775          | 0.5111   |
| 0.8756        | 28.0  | 756  | 1.1755          | 0.5111   |
| 0.8844        | 29.0  | 783  | 1.1704          | 0.5111   |
| 0.9306        | 30.0  | 810  | 1.1638          | 0.4889   |
| 0.8332        | 31.0  | 837  | 1.1571          | 0.4889   |
| 0.8854        | 32.0  | 864  | 1.1562          | 0.4889   |
| 0.869         | 33.0  | 891  | 1.1538          | 0.4889   |
| 0.8165        | 34.0  | 918  | 1.1565          | 0.4889   |
| 0.8544        | 35.0  | 945  | 1.1478          | 0.4889   |
| 0.7949        | 36.0  | 972  | 1.1509          | 0.4889   |
| 0.7913        | 37.0  | 999  | 1.1517          | 0.4889   |
| 0.8304        | 38.0  | 1026 | 1.1504          | 0.4889   |
| 0.8034        | 39.0  | 1053 | 1.1530          | 0.5111   |
| 0.7958        | 40.0  | 1080 | 1.1506          | 0.4889   |
| 0.7773        | 41.0  | 1107 | 1.1491          | 0.5111   |
| 0.7795        | 42.0  | 1134 | 1.1490          | 0.5111   |
| 0.8191        | 43.0  | 1161 | 1.1489          | 0.5111   |
| 0.7893        | 44.0  | 1188 | 1.1487          | 0.5111   |
| 0.8109        | 45.0  | 1215 | 1.1476          | 0.5111   |
| 0.7952        | 46.0  | 1242 | 1.1473          | 0.5111   |
| 0.798         | 47.0  | 1269 | 1.1472          | 0.5111   |
| 0.8109        | 48.0  | 1296 | 1.1467          | 0.5111   |
| 0.8173        | 49.0  | 1323 | 1.1467          | 0.5111   |
| 0.7998        | 50.0  | 1350 | 1.1467          | 0.5111   |


### 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_sgd_001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5111111111111111, "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