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# HUSHEM_5x_beit_large_RMSProp_lr0001_fold4

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: 2.9539
- Accuracy: 0.7619

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4182        | 1.0   | 55   | 1.2614          | 0.2857   |
| 1.3101        | 2.0   | 110  | 1.0707          | 0.5      |
| 1.5364        | 3.0   | 165  | 1.4966          | 0.2381   |
| 1.0022        | 4.0   | 220  | 0.7708          | 0.6190   |
| 0.929         | 5.0   | 275  | 0.5381          | 0.7857   |
| 0.8557        | 6.0   | 330  | 0.5683          | 0.7857   |
| 0.8824        | 7.0   | 385  | 0.7703          | 0.7619   |
| 0.9669        | 8.0   | 440  | 0.6917          | 0.7381   |
| 0.8595        | 9.0   | 495  | 0.6058          | 0.7381   |
| 0.8634        | 10.0  | 550  | 0.9602          | 0.5952   |
| 0.732         | 11.0  | 605  | 0.7438          | 0.7857   |
| 0.8007        | 12.0  | 660  | 0.5907          | 0.8333   |
| 0.695         | 13.0  | 715  | 0.7216          | 0.7381   |
| 0.7466        | 14.0  | 770  | 1.2445          | 0.6667   |
| 0.6738        | 15.0  | 825  | 0.6668          | 0.7143   |
| 0.6202        | 16.0  | 880  | 0.9476          | 0.7143   |
| 0.7321        | 17.0  | 935  | 0.7180          | 0.7857   |
| 0.4932        | 18.0  | 990  | 1.1175          | 0.7143   |
| 0.5138        | 19.0  | 1045 | 0.6529          | 0.8095   |
| 0.5615        | 20.0  | 1100 | 1.0204          | 0.7143   |
| 0.518         | 21.0  | 1155 | 0.8295          | 0.7143   |
| 0.4912        | 22.0  | 1210 | 1.1563          | 0.7143   |
| 0.4442        | 23.0  | 1265 | 0.9194          | 0.7857   |
| 0.3428        | 24.0  | 1320 | 1.2434          | 0.6667   |
| 0.3618        | 25.0  | 1375 | 1.3185          | 0.7381   |
| 0.3569        | 26.0  | 1430 | 1.0756          | 0.6905   |
| 0.2794        | 27.0  | 1485 | 1.2624          | 0.7143   |
| 0.2875        | 28.0  | 1540 | 0.8476          | 0.8333   |
| 0.242         | 29.0  | 1595 | 1.5263          | 0.7381   |
| 0.3213        | 30.0  | 1650 | 1.4379          | 0.7381   |
| 0.2845        | 31.0  | 1705 | 1.0304          | 0.7143   |
| 0.1987        | 32.0  | 1760 | 1.3217          | 0.7381   |
| 0.1844        | 33.0  | 1815 | 1.5492          | 0.7619   |
| 0.253         | 34.0  | 1870 | 1.2128          | 0.8095   |
| 0.0742        | 35.0  | 1925 | 1.6972          | 0.8095   |
| 0.086         | 36.0  | 1980 | 1.8817          | 0.6905   |
| 0.0363        | 37.0  | 2035 | 1.6723          | 0.7381   |
| 0.017         | 38.0  | 2090 | 2.0662          | 0.7857   |
| 0.0373        | 39.0  | 2145 | 2.4771          | 0.7143   |
| 0.0827        | 40.0  | 2200 | 3.1485          | 0.6667   |
| 0.1127        | 41.0  | 2255 | 2.6221          | 0.7381   |
| 0.1063        | 42.0  | 2310 | 3.5269          | 0.7143   |
| 0.0436        | 43.0  | 2365 | 2.8465          | 0.7143   |
| 0.0004        | 44.0  | 2420 | 3.4317          | 0.7143   |
| 0.0492        | 45.0  | 2475 | 3.0784          | 0.6667   |
| 0.0006        | 46.0  | 2530 | 2.9686          | 0.7381   |
| 0.0169        | 47.0  | 2585 | 3.0629          | 0.7619   |
| 0.074         | 48.0  | 2640 | 3.0441          | 0.7381   |
| 0.0168        | 49.0  | 2695 | 2.9539          | 0.7619   |
| 0.0           | 50.0  | 2750 | 2.9539          | 0.7619   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7619047619047619, "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