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# HUSHEM_5x_beit_large_RMSProp_lr0001_fold3

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: 4.0143
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4091        | 1.0   | 55   | 1.6391          | 0.2558   |
| 1.2716        | 2.0   | 110  | 1.1183          | 0.5349   |
| 0.9861        | 3.0   | 165  | 0.6856          | 0.7442   |
| 1.0673        | 4.0   | 220  | 0.7625          | 0.7674   |
| 0.8384        | 5.0   | 275  | 0.6710          | 0.7209   |
| 1.0219        | 6.0   | 330  | 1.0503          | 0.4651   |
| 0.8388        | 7.0   | 385  | 0.8702          | 0.7907   |
| 0.9198        | 8.0   | 440  | 0.7126          | 0.7907   |
| 0.7543        | 9.0   | 495  | 0.9101          | 0.7674   |
| 0.8021        | 10.0  | 550  | 1.0358          | 0.4651   |
| 0.6809        | 11.0  | 605  | 0.6671          | 0.7442   |
| 0.6095        | 12.0  | 660  | 1.3237          | 0.6512   |
| 0.6364        | 13.0  | 715  | 0.8265          | 0.6512   |
| 0.5471        | 14.0  | 770  | 0.7501          | 0.6977   |
| 0.7123        | 15.0  | 825  | 0.7796          | 0.6977   |
| 0.4506        | 16.0  | 880  | 1.0639          | 0.6512   |
| 0.5385        | 17.0  | 935  | 1.5341          | 0.5116   |
| 0.3986        | 18.0  | 990  | 1.1557          | 0.6047   |
| 0.3922        | 19.0  | 1045 | 1.5637          | 0.5581   |
| 0.4818        | 20.0  | 1100 | 1.6356          | 0.5349   |
| 0.5569        | 21.0  | 1155 | 1.2807          | 0.6279   |
| 0.3119        | 22.0  | 1210 | 1.4191          | 0.6047   |
| 0.3124        | 23.0  | 1265 | 1.4038          | 0.6512   |
| 0.3503        | 24.0  | 1320 | 1.4008          | 0.6512   |
| 0.3745        | 25.0  | 1375 | 0.9195          | 0.7442   |
| 0.2816        | 26.0  | 1430 | 1.9693          | 0.6512   |
| 0.2827        | 27.0  | 1485 | 2.5188          | 0.5814   |
| 0.3658        | 28.0  | 1540 | 2.8996          | 0.6279   |
| 0.1667        | 29.0  | 1595 | 2.6130          | 0.5581   |
| 0.1658        | 30.0  | 1650 | 2.3416          | 0.5581   |
| 0.1395        | 31.0  | 1705 | 2.9218          | 0.5349   |
| 0.0949        | 32.0  | 1760 | 3.4289          | 0.6512   |
| 0.1876        | 33.0  | 1815 | 2.8052          | 0.6512   |
| 0.0597        | 34.0  | 1870 | 4.3533          | 0.6279   |
| 0.1927        | 35.0  | 1925 | 3.3070          | 0.5814   |
| 0.092         | 36.0  | 1980 | 3.2418          | 0.6047   |
| 0.0737        | 37.0  | 2035 | 3.4604          | 0.5814   |
| 0.0412        | 38.0  | 2090 | 4.3049          | 0.5581   |
| 0.0265        | 39.0  | 2145 | 3.8457          | 0.6512   |
| 0.0073        | 40.0  | 2200 | 4.6464          | 0.5349   |
| 0.0015        | 41.0  | 2255 | 4.6719          | 0.5581   |
| 0.0855        | 42.0  | 2310 | 3.5201          | 0.6047   |
| 0.0178        | 43.0  | 2365 | 4.3315          | 0.6512   |
| 0.0011        | 44.0  | 2420 | 4.0044          | 0.6512   |
| 0.0106        | 45.0  | 2475 | 4.4584          | 0.6512   |
| 0.0011        | 46.0  | 2530 | 4.3786          | 0.6279   |
| 0.0016        | 47.0  | 2585 | 4.2096          | 0.6279   |
| 0.0167        | 48.0  | 2640 | 3.8908          | 0.6744   |
| 0.0144        | 49.0  | 2695 | 4.0143          | 0.6744   |
| 0.0473        | 50.0  | 2750 | 4.0143          | 0.6744   |


### 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_5x_beit_large_RMSProp_lr0001_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 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