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# hushem_5x_beit_base_rms_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: 2.4962
- Accuracy: 0.3415

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.501         | 1.0   | 28   | 1.3919          | 0.2439   |
| 1.3993        | 2.0   | 56   | 1.4008          | 0.2683   |
| 1.4258        | 3.0   | 84   | 1.4098          | 0.2439   |
| 1.4011        | 4.0   | 112  | 1.3674          | 0.2683   |
| 1.4153        | 5.0   | 140  | 1.3306          | 0.2683   |
| 1.3649        | 6.0   | 168  | 1.4784          | 0.2195   |
| 1.3525        | 7.0   | 196  | 1.2906          | 0.4390   |
| 1.3374        | 8.0   | 224  | 1.1798          | 0.5122   |
| 1.2661        | 9.0   | 252  | 1.3479          | 0.5122   |
| 1.3011        | 10.0  | 280  | 1.3054          | 0.4878   |
| 1.2212        | 11.0  | 308  | 1.1612          | 0.5122   |
| 1.2579        | 12.0  | 336  | 1.2572          | 0.2683   |
| 1.2438        | 13.0  | 364  | 1.1160          | 0.4634   |
| 1.2218        | 14.0  | 392  | 1.1291          | 0.4878   |
| 1.2455        | 15.0  | 420  | 1.4587          | 0.4390   |
| 1.2528        | 16.0  | 448  | 1.3009          | 0.5122   |
| 1.2445        | 17.0  | 476  | 1.1915          | 0.5122   |
| 1.1729        | 18.0  | 504  | 1.3461          | 0.4390   |
| 1.2917        | 19.0  | 532  | 1.3956          | 0.3659   |
| 1.2335        | 20.0  | 560  | 1.1161          | 0.4146   |
| 1.1787        | 21.0  | 588  | 1.4220          | 0.4390   |
| 1.1076        | 22.0  | 616  | 1.2157          | 0.5122   |
| 1.1837        | 23.0  | 644  | 1.2878          | 0.4634   |
| 1.065         | 24.0  | 672  | 1.3373          | 0.3659   |
| 1.0753        | 25.0  | 700  | 1.2968          | 0.4634   |
| 1.0288        | 26.0  | 728  | 1.2996          | 0.4146   |
| 1.0679        | 27.0  | 756  | 1.2975          | 0.3902   |
| 1.0591        | 28.0  | 784  | 1.3051          | 0.4634   |
| 1.0148        | 29.0  | 812  | 1.2575          | 0.5854   |
| 1.0668        | 30.0  | 840  | 1.3174          | 0.3415   |
| 0.9767        | 31.0  | 868  | 1.3259          | 0.4390   |
| 0.9254        | 32.0  | 896  | 1.3236          | 0.4878   |
| 0.9064        | 33.0  | 924  | 1.5265          | 0.3902   |
| 0.9504        | 34.0  | 952  | 1.2456          | 0.4390   |
| 0.8534        | 35.0  | 980  | 1.2811          | 0.5122   |
| 0.8361        | 36.0  | 1008 | 1.2101          | 0.6098   |
| 0.7846        | 37.0  | 1036 | 1.3727          | 0.4390   |
| 0.7661        | 38.0  | 1064 | 1.4030          | 0.4878   |
| 0.8237        | 39.0  | 1092 | 1.3385          | 0.4634   |
| 0.7652        | 40.0  | 1120 | 1.6174          | 0.4146   |
| 0.6764        | 41.0  | 1148 | 1.6358          | 0.4390   |
| 0.5675        | 42.0  | 1176 | 1.7675          | 0.4390   |
| 0.5777        | 43.0  | 1204 | 1.8573          | 0.4390   |
| 0.5704        | 44.0  | 1232 | 2.0252          | 0.3902   |
| 0.5677        | 45.0  | 1260 | 2.0725          | 0.3902   |
| 0.4676        | 46.0  | 1288 | 2.4159          | 0.3171   |
| 0.4167        | 47.0  | 1316 | 2.4083          | 0.3415   |
| 0.416         | 48.0  | 1344 | 2.4826          | 0.3415   |
| 0.3715        | 49.0  | 1372 | 2.4962          | 0.3415   |
| 0.368         | 50.0  | 1400 | 2.4962          | 0.3415   |


### 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_rms_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": 0.34146341463414637, "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