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# hushem_5x_beit_base_rms_0001_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: 3.4047
- 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4155        | 1.0   | 28   | 1.3777          | 0.2683   |
| 1.3848        | 2.0   | 56   | 1.2989          | 0.2927   |
| 1.3314        | 3.0   | 84   | 1.2733          | 0.4878   |
| 1.2486        | 4.0   | 112  | 1.0811          | 0.5122   |
| 1.2007        | 5.0   | 140  | 0.9236          | 0.5854   |
| 1.05          | 6.0   | 168  | 1.1380          | 0.5122   |
| 1.0162        | 7.0   | 196  | 0.9574          | 0.5854   |
| 0.9476        | 8.0   | 224  | 1.4400          | 0.4878   |
| 0.903         | 9.0   | 252  | 0.9012          | 0.6341   |
| 0.9351        | 10.0  | 280  | 1.0183          | 0.6829   |
| 0.8113        | 11.0  | 308  | 0.9612          | 0.6585   |
| 0.8131        | 12.0  | 336  | 1.6631          | 0.4878   |
| 0.7921        | 13.0  | 364  | 0.9316          | 0.6829   |
| 0.8114        | 14.0  | 392  | 1.3372          | 0.5854   |
| 0.7382        | 15.0  | 420  | 1.4796          | 0.6341   |
| 0.7119        | 16.0  | 448  | 1.9753          | 0.5366   |
| 0.6933        | 17.0  | 476  | 1.3458          | 0.7073   |
| 0.591         | 18.0  | 504  | 1.3968          | 0.6585   |
| 0.6986        | 19.0  | 532  | 1.4904          | 0.6829   |
| 0.6832        | 20.0  | 560  | 1.7362          | 0.6585   |
| 0.5173        | 21.0  | 588  | 1.5475          | 0.7317   |
| 0.5116        | 22.0  | 616  | 1.9547          | 0.6585   |
| 0.4833        | 23.0  | 644  | 2.1246          | 0.6341   |
| 0.4295        | 24.0  | 672  | 1.9058          | 0.7317   |
| 0.4431        | 25.0  | 700  | 2.4495          | 0.6585   |
| 0.3801        | 26.0  | 728  | 1.6867          | 0.7561   |
| 0.4263        | 27.0  | 756  | 2.1056          | 0.6585   |
| 0.3209        | 28.0  | 784  | 2.6127          | 0.6098   |
| 0.29          | 29.0  | 812  | 2.2833          | 0.6341   |
| 0.2306        | 30.0  | 840  | 2.6477          | 0.6341   |
| 0.2318        | 31.0  | 868  | 2.2205          | 0.6829   |
| 0.1766        | 32.0  | 896  | 2.1057          | 0.8293   |
| 0.1861        | 33.0  | 924  | 2.9102          | 0.6341   |
| 0.2172        | 34.0  | 952  | 2.3319          | 0.7317   |
| 0.1336        | 35.0  | 980  | 2.7931          | 0.7073   |
| 0.128         | 36.0  | 1008 | 3.2544          | 0.6098   |
| 0.1009        | 37.0  | 1036 | 2.3057          | 0.7805   |
| 0.1495        | 38.0  | 1064 | 2.9047          | 0.7317   |
| 0.0845        | 39.0  | 1092 | 3.1290          | 0.7317   |
| 0.064         | 40.0  | 1120 | 2.9682          | 0.7561   |
| 0.0399        | 41.0  | 1148 | 2.9364          | 0.7561   |
| 0.0198        | 42.0  | 1176 | 4.0340          | 0.6585   |
| 0.0179        | 43.0  | 1204 | 3.2313          | 0.7317   |
| 0.0799        | 44.0  | 1232 | 3.4340          | 0.7317   |
| 0.0495        | 45.0  | 1260 | 3.8737          | 0.6829   |
| 0.041         | 46.0  | 1288 | 3.5139          | 0.6829   |
| 0.0058        | 47.0  | 1316 | 3.4146          | 0.7073   |
| 0.0141        | 48.0  | 1344 | 3.4016          | 0.7073   |
| 0.0316        | 49.0  | 1372 | 3.4047          | 0.7073   |
| 0.0269        | 50.0  | 1400 | 3.4047          | 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_rms_0001_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