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# HUSHEM_5x_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: 2.1556
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3866        | 1.0   | 55   | 1.3332          | 0.2439   |
| 1.289         | 2.0   | 110  | 1.1701          | 0.5610   |
| 1.1118        | 3.0   | 165  | 0.8052          | 0.6341   |
| 0.8735        | 4.0   | 220  | 1.2780          | 0.5854   |
| 0.9683        | 5.0   | 275  | 0.8966          | 0.5854   |
| 1.2381        | 6.0   | 330  | 1.1185          | 0.7073   |
| 0.8451        | 7.0   | 385  | 0.8541          | 0.5854   |
| 0.8435        | 8.0   | 440  | 1.0196          | 0.6098   |
| 0.8024        | 9.0   | 495  | 0.6139          | 0.7561   |
| 0.7554        | 10.0  | 550  | 0.6374          | 0.6829   |
| 0.6942        | 11.0  | 605  | 0.7996          | 0.7561   |
| 0.8877        | 12.0  | 660  | 0.9569          | 0.7317   |
| 0.7463        | 13.0  | 715  | 0.7710          | 0.7317   |
| 0.6023        | 14.0  | 770  | 1.1420          | 0.6585   |
| 0.7005        | 15.0  | 825  | 0.7149          | 0.7317   |
| 0.6202        | 16.0  | 880  | 0.8834          | 0.7561   |
| 0.6217        | 17.0  | 935  | 0.7110          | 0.7317   |
| 0.5084        | 18.0  | 990  | 1.1760          | 0.6341   |
| 0.6003        | 19.0  | 1045 | 1.0859          | 0.7317   |
| 0.5349        | 20.0  | 1100 | 1.0746          | 0.6829   |
| 0.4927        | 21.0  | 1155 | 1.2363          | 0.6829   |
| 0.4969        | 22.0  | 1210 | 0.9474          | 0.8049   |
| 0.4247        | 23.0  | 1265 | 1.6726          | 0.7073   |
| 0.3272        | 24.0  | 1320 | 1.8425          | 0.7073   |
| 0.3705        | 25.0  | 1375 | 1.1214          | 0.7073   |
| 0.3321        | 26.0  | 1430 | 1.4469          | 0.7073   |
| 0.2647        | 27.0  | 1485 | 1.9545          | 0.7073   |
| 0.3202        | 28.0  | 1540 | 1.5849          | 0.7805   |
| 0.2432        | 29.0  | 1595 | 1.6719          | 0.7317   |
| 0.4013        | 30.0  | 1650 | 1.6273          | 0.7317   |
| 0.3028        | 31.0  | 1705 | 1.6028          | 0.7073   |
| 0.1725        | 32.0  | 1760 | 1.9589          | 0.7073   |
| 0.2694        | 33.0  | 1815 | 1.8798          | 0.6585   |
| 0.2545        | 34.0  | 1870 | 1.4244          | 0.7073   |
| 0.1627        | 35.0  | 1925 | 1.8655          | 0.7073   |
| 0.225         | 36.0  | 1980 | 1.7493          | 0.7561   |
| 0.1498        | 37.0  | 2035 | 1.8871          | 0.7317   |
| 0.1219        | 38.0  | 2090 | 1.9154          | 0.7073   |
| 0.0653        | 39.0  | 2145 | 2.6480          | 0.7073   |
| 0.0227        | 40.0  | 2200 | 2.1018          | 0.7317   |
| 0.0911        | 41.0  | 2255 | 2.8035          | 0.7073   |
| 0.114         | 42.0  | 2310 | 2.3199          | 0.7317   |
| 0.0794        | 43.0  | 2365 | 2.4262          | 0.7317   |
| 0.0338        | 44.0  | 2420 | 2.4291          | 0.6829   |
| 0.0563        | 45.0  | 2475 | 2.2609          | 0.6829   |
| 0.0385        | 46.0  | 2530 | 2.1357          | 0.7317   |
| 0.0026        | 47.0  | 2585 | 2.1533          | 0.7073   |
| 0.0589        | 48.0  | 2640 | 2.1040          | 0.7317   |
| 0.0458        | 49.0  | 2695 | 2.1555          | 0.7317   |
| 0.0575        | 50.0  | 2750 | 2.1556          | 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_5x_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