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# hushem_5x_beit_base_rms_0001_fold4

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: 1.8159
- Accuracy: 0.7857

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4247        | 1.0   | 28   | 1.3411          | 0.2381   |
| 1.3595        | 2.0   | 56   | 1.2501          | 0.4286   |
| 1.3116        | 3.0   | 84   | 1.5240          | 0.2381   |
| 1.303         | 4.0   | 112  | 1.0491          | 0.5238   |
| 1.1942        | 5.0   | 140  | 0.8861          | 0.7143   |
| 1.1712        | 6.0   | 168  | 0.9106          | 0.5238   |
| 0.977         | 7.0   | 196  | 1.1447          | 0.6905   |
| 0.9351        | 8.0   | 224  | 0.7191          | 0.7619   |
| 0.8453        | 9.0   | 252  | 1.3331          | 0.5714   |
| 0.8831        | 10.0  | 280  | 0.8305          | 0.6905   |
| 0.8349        | 11.0  | 308  | 0.6872          | 0.7619   |
| 0.845         | 12.0  | 336  | 0.7545          | 0.7619   |
| 0.784         | 13.0  | 364  | 0.7961          | 0.7857   |
| 0.7404        | 14.0  | 392  | 0.6338          | 0.8095   |
| 0.6277        | 15.0  | 420  | 0.7200          | 0.7143   |
| 0.6386        | 16.0  | 448  | 0.7383          | 0.8095   |
| 0.6167        | 17.0  | 476  | 0.5440          | 0.8095   |
| 0.5129        | 18.0  | 504  | 0.7061          | 0.7619   |
| 0.3836        | 19.0  | 532  | 0.7181          | 0.7381   |
| 0.3202        | 20.0  | 560  | 0.4277          | 0.8095   |
| 0.1958        | 21.0  | 588  | 1.1637          | 0.7381   |
| 0.2343        | 22.0  | 616  | 1.0581          | 0.8095   |
| 0.2016        | 23.0  | 644  | 0.8968          | 0.7857   |
| 0.116         | 24.0  | 672  | 1.0426          | 0.7857   |
| 0.1027        | 25.0  | 700  | 0.6841          | 0.8333   |
| 0.1133        | 26.0  | 728  | 0.8260          | 0.8095   |
| 0.1258        | 27.0  | 756  | 1.3215          | 0.7619   |
| 0.0595        | 28.0  | 784  | 1.0509          | 0.8810   |
| 0.0945        | 29.0  | 812  | 1.3868          | 0.7857   |
| 0.0022        | 30.0  | 840  | 1.7553          | 0.8095   |
| 0.0004        | 31.0  | 868  | 1.9423          | 0.7857   |
| 0.0466        | 32.0  | 896  | 2.0945          | 0.8095   |
| 0.0367        | 33.0  | 924  | 1.6928          | 0.8095   |
| 0.1032        | 34.0  | 952  | 1.3572          | 0.8571   |
| 0.0331        | 35.0  | 980  | 2.0437          | 0.8095   |
| 0.0001        | 36.0  | 1008 | 2.0414          | 0.8333   |
| 0.0286        | 37.0  | 1036 | 2.0546          | 0.7619   |
| 0.009         | 38.0  | 1064 | 2.8381          | 0.7857   |
| 0.0573        | 39.0  | 1092 | 2.4470          | 0.7857   |
| 0.0497        | 40.0  | 1120 | 1.8192          | 0.7857   |
| 0.0003        | 41.0  | 1148 | 2.1421          | 0.7143   |
| 0.0003        | 42.0  | 1176 | 2.2125          | 0.7381   |
| 0.0001        | 43.0  | 1204 | 2.1555          | 0.7619   |
| 0.0002        | 44.0  | 1232 | 1.8154          | 0.7381   |
| 0.0197        | 45.0  | 1260 | 1.7188          | 0.7381   |
| 0.0002        | 46.0  | 1288 | 1.6637          | 0.8095   |
| 0.0152        | 47.0  | 1316 | 1.6954          | 0.8095   |
| 0.0001        | 48.0  | 1344 | 1.8153          | 0.7857   |
| 0.0002        | 49.0  | 1372 | 1.8159          | 0.7857   |
| 0.0           | 50.0  | 1400 | 1.8159          | 0.7857   |


### 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_0001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7857142857142857, "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