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# hushem_5x_beit_base_rms_0001_fold3

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: 2.0271
- Accuracy: 0.6744

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4187        | 1.0   | 28   | 1.4291          | 0.2558   |
| 1.401         | 2.0   | 56   | 1.4569          | 0.2558   |
| 1.367         | 3.0   | 84   | 1.2989          | 0.2791   |
| 1.3068        | 4.0   | 112  | 1.1706          | 0.5116   |
| 1.282         | 5.0   | 140  | 1.1869          | 0.5581   |
| 1.1177        | 6.0   | 168  | 0.8916          | 0.7442   |
| 0.8904        | 7.0   | 196  | 0.7798          | 0.7209   |
| 0.9449        | 8.0   | 224  | 0.6587          | 0.7674   |
| 0.8708        | 9.0   | 252  | 1.0524          | 0.5814   |
| 0.9352        | 10.0  | 280  | 0.7664          | 0.6744   |
| 0.8718        | 11.0  | 308  | 0.6191          | 0.7907   |
| 0.7977        | 12.0  | 336  | 1.1991          | 0.6512   |
| 0.8081        | 13.0  | 364  | 0.7062          | 0.7674   |
| 0.7399        | 14.0  | 392  | 0.7130          | 0.6744   |
| 0.8202        | 15.0  | 420  | 0.7484          | 0.6977   |
| 0.7069        | 16.0  | 448  | 0.6665          | 0.6977   |
| 0.6169        | 17.0  | 476  | 0.7828          | 0.6279   |
| 0.6766        | 18.0  | 504  | 0.9849          | 0.5814   |
| 0.6876        | 19.0  | 532  | 0.7015          | 0.7442   |
| 0.5123        | 20.0  | 560  | 0.9230          | 0.7442   |
| 0.4885        | 21.0  | 588  | 0.9671          | 0.6279   |
| 0.5212        | 22.0  | 616  | 1.2712          | 0.6744   |
| 0.5047        | 23.0  | 644  | 0.7902          | 0.6512   |
| 0.4047        | 24.0  | 672  | 1.3996          | 0.7209   |
| 0.361         | 25.0  | 700  | 1.1508          | 0.6279   |
| 0.362         | 26.0  | 728  | 1.0709          | 0.6279   |
| 0.3752        | 27.0  | 756  | 0.9894          | 0.6512   |
| 0.2958        | 28.0  | 784  | 1.2219          | 0.6279   |
| 0.3016        | 29.0  | 812  | 0.8154          | 0.6977   |
| 0.2083        | 30.0  | 840  | 1.2432          | 0.6047   |
| 0.2249        | 31.0  | 868  | 1.5401          | 0.6047   |
| 0.1443        | 32.0  | 896  | 1.3193          | 0.6279   |
| 0.1501        | 33.0  | 924  | 1.1707          | 0.6977   |
| 0.1715        | 34.0  | 952  | 1.1677          | 0.7442   |
| 0.2795        | 35.0  | 980  | 1.2992          | 0.6744   |
| 0.1174        | 36.0  | 1008 | 1.6643          | 0.6744   |
| 0.1132        | 37.0  | 1036 | 1.7522          | 0.6279   |
| 0.0738        | 38.0  | 1064 | 1.6182          | 0.6744   |
| 0.0433        | 39.0  | 1092 | 2.1223          | 0.6512   |
| 0.0483        | 40.0  | 1120 | 2.5522          | 0.5814   |
| 0.0333        | 41.0  | 1148 | 1.8374          | 0.6977   |
| 0.0107        | 42.0  | 1176 | 1.9629          | 0.6744   |
| 0.013         | 43.0  | 1204 | 1.6900          | 0.7209   |
| 0.0316        | 44.0  | 1232 | 2.1881          | 0.6512   |
| 0.0272        | 45.0  | 1260 | 1.8428          | 0.6744   |
| 0.0298        | 46.0  | 1288 | 1.7049          | 0.7674   |
| 0.0196        | 47.0  | 1316 | 1.9117          | 0.6744   |
| 0.0084        | 48.0  | 1344 | 2.0336          | 0.6744   |
| 0.0059        | 49.0  | 1372 | 2.0271          | 0.6744   |
| 0.0065        | 50.0  | 1400 | 2.0271          | 0.6744   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6744186046511628, "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