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# HUSHEM_10x_beit_large_RMSProp_lr0001_fold5

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1995
- Accuracy: 0.7317

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2843        | 1.0   | 110  | 1.3724          | 0.2683   |
| 1.0715        | 2.0   | 220  | 0.8712          | 0.5854   |
| 0.9856        | 3.0   | 330  | 0.9681          | 0.6098   |
| 1.0038        | 4.0   | 440  | 0.8256          | 0.6829   |
| 0.8765        | 5.0   | 550  | 0.8305          | 0.6829   |
| 0.8711        | 6.0   | 660  | 1.0156          | 0.6829   |
| 0.8304        | 7.0   | 770  | 0.6931          | 0.7805   |
| 0.8426        | 8.0   | 880  | 0.8435          | 0.7317   |
| 0.8233        | 9.0   | 990  | 1.0327          | 0.5610   |
| 0.7841        | 10.0  | 1100 | 0.7480          | 0.7561   |
| 0.9232        | 11.0  | 1210 | 0.7659          | 0.7073   |
| 0.8074        | 12.0  | 1320 | 1.1038          | 0.6341   |
| 0.7954        | 13.0  | 1430 | 0.6300          | 0.7805   |
| 0.6267        | 14.0  | 1540 | 0.9022          | 0.6829   |
| 0.4997        | 15.0  | 1650 | 0.8514          | 0.7073   |
| 0.7083        | 16.0  | 1760 | 0.7196          | 0.7561   |
| 0.5384        | 17.0  | 1870 | 0.7236          | 0.7317   |
| 0.5216        | 18.0  | 1980 | 1.1330          | 0.7317   |
| 0.4079        | 19.0  | 2090 | 0.6848          | 0.8293   |
| 0.3676        | 20.0  | 2200 | 1.2296          | 0.7805   |
| 0.2886        | 21.0  | 2310 | 0.8384          | 0.6585   |
| 0.3757        | 22.0  | 2420 | 1.0965          | 0.6585   |
| 0.3893        | 23.0  | 2530 | 1.0829          | 0.7317   |
| 0.2802        | 24.0  | 2640 | 1.2958          | 0.6585   |
| 0.2392        | 25.0  | 2750 | 0.8171          | 0.7317   |
| 0.227         | 26.0  | 2860 | 1.9211          | 0.6585   |
| 0.2095        | 27.0  | 2970 | 0.9051          | 0.7561   |
| 0.2096        | 28.0  | 3080 | 1.7406          | 0.7805   |
| 0.1698        | 29.0  | 3190 | 1.2372          | 0.7317   |
| 0.1485        | 30.0  | 3300 | 1.6047          | 0.7317   |
| 0.2134        | 31.0  | 3410 | 2.4136          | 0.6098   |
| 0.0772        | 32.0  | 3520 | 1.6681          | 0.7073   |
| 0.0947        | 33.0  | 3630 | 2.1472          | 0.7317   |
| 0.0584        | 34.0  | 3740 | 1.9550          | 0.7073   |
| 0.1605        | 35.0  | 3850 | 2.8741          | 0.7317   |
| 0.0329        | 36.0  | 3960 | 2.4980          | 0.8049   |
| 0.0593        | 37.0  | 4070 | 2.8810          | 0.7805   |
| 0.0771        | 38.0  | 4180 | 3.3865          | 0.7561   |
| 0.0472        | 39.0  | 4290 | 3.3879          | 0.7073   |
| 0.0344        | 40.0  | 4400 | 1.9451          | 0.7317   |
| 0.0488        | 41.0  | 4510 | 2.6713          | 0.7805   |
| 0.0203        | 42.0  | 4620 | 3.0985          | 0.7073   |
| 0.0775        | 43.0  | 4730 | 2.2879          | 0.7561   |
| 0.0107        | 44.0  | 4840 | 2.6263          | 0.7561   |
| 0.0072        | 45.0  | 4950 | 2.8287          | 0.7073   |
| 0.0085        | 46.0  | 5060 | 2.9952          | 0.7561   |
| 0.0052        | 47.0  | 5170 | 3.1468          | 0.6829   |
| 0.0282        | 48.0  | 5280 | 3.4275          | 0.7317   |
| 0.0           | 49.0  | 5390 | 3.2045          | 0.7317   |
| 0.0002        | 50.0  | 5500 | 3.1995          | 0.7317   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "HUSHEM_10x_beit_large_RMSProp_lr0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7317073170731707, "name": "Accuracy"}]}]}]}
transformers pytorch beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-large-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us