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# hushem_5x_beit_base_sgd_001_fold5

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: 0.8979
- Accuracy: 0.7073

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5363        | 1.0   | 28   | 1.5515          | 0.2439   |
| 1.4164        | 2.0   | 56   | 1.4971          | 0.3171   |
| 1.362         | 3.0   | 84   | 1.4523          | 0.3659   |
| 1.3381        | 4.0   | 112  | 1.3987          | 0.3902   |
| 1.2805        | 5.0   | 140  | 1.3538          | 0.4390   |
| 1.286         | 6.0   | 168  | 1.3184          | 0.4634   |
| 1.2664        | 7.0   | 196  | 1.2890          | 0.4634   |
| 1.1752        | 8.0   | 224  | 1.2605          | 0.4878   |
| 1.1615        | 9.0   | 252  | 1.2357          | 0.5366   |
| 1.1583        | 10.0  | 280  | 1.2200          | 0.5366   |
| 1.0622        | 11.0  | 308  | 1.1865          | 0.5854   |
| 1.0888        | 12.0  | 336  | 1.1579          | 0.5854   |
| 1.0774        | 13.0  | 364  | 1.1376          | 0.6098   |
| 1.0639        | 14.0  | 392  | 1.1207          | 0.6098   |
| 1.0329        | 15.0  | 420  | 1.1063          | 0.6098   |
| 1.0224        | 16.0  | 448  | 1.0819          | 0.6098   |
| 0.9888        | 17.0  | 476  | 1.0775          | 0.6098   |
| 0.9619        | 18.0  | 504  | 1.0585          | 0.6098   |
| 0.9636        | 19.0  | 532  | 1.0418          | 0.6098   |
| 0.932         | 20.0  | 560  | 1.0228          | 0.6098   |
| 0.9605        | 21.0  | 588  | 1.0275          | 0.6341   |
| 0.9245        | 22.0  | 616  | 1.0007          | 0.6829   |
| 0.9128        | 23.0  | 644  | 0.9952          | 0.6829   |
| 0.8833        | 24.0  | 672  | 0.9964          | 0.6585   |
| 0.8669        | 25.0  | 700  | 0.9755          | 0.6829   |
| 0.8822        | 26.0  | 728  | 0.9683          | 0.6829   |
| 0.8736        | 27.0  | 756  | 0.9644          | 0.6829   |
| 0.8195        | 28.0  | 784  | 0.9503          | 0.6829   |
| 0.815         | 29.0  | 812  | 0.9479          | 0.6829   |
| 0.8347        | 30.0  | 840  | 0.9483          | 0.6829   |
| 0.8334        | 31.0  | 868  | 0.9382          | 0.6829   |
| 0.7989        | 32.0  | 896  | 0.9378          | 0.6829   |
| 0.7878        | 33.0  | 924  | 0.9468          | 0.6829   |
| 0.8479        | 34.0  | 952  | 0.9186          | 0.7073   |
| 0.7868        | 35.0  | 980  | 0.9253          | 0.6829   |
| 0.7921        | 36.0  | 1008 | 0.9134          | 0.7073   |
| 0.7563        | 37.0  | 1036 | 0.9054          | 0.7073   |
| 0.7507        | 38.0  | 1064 | 0.9071          | 0.7073   |
| 0.8331        | 39.0  | 1092 | 0.8998          | 0.7073   |
| 0.7104        | 40.0  | 1120 | 0.9052          | 0.7073   |
| 0.773         | 41.0  | 1148 | 0.9044          | 0.7073   |
| 0.719         | 42.0  | 1176 | 0.9021          | 0.7073   |
| 0.7745        | 43.0  | 1204 | 0.8997          | 0.7073   |
| 0.781         | 44.0  | 1232 | 0.9016          | 0.7073   |
| 0.755         | 45.0  | 1260 | 0.9002          | 0.7073   |
| 0.7437        | 46.0  | 1288 | 0.9000          | 0.7073   |
| 0.7695        | 47.0  | 1316 | 0.8981          | 0.7073   |
| 0.7339        | 48.0  | 1344 | 0.8980          | 0.7073   |
| 0.7563        | 49.0  | 1372 | 0.8979          | 0.7073   |
| 0.755         | 50.0  | 1400 | 0.8979          | 0.7073   |


### 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_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7073170731707317, "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