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# HUSHEM_5x_beit_large_SGD_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: 1.2411
- Accuracy: 0.4390

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5133        | 1.0   | 55   | 1.5465          | 0.2439   |
| 1.5672        | 2.0   | 110  | 1.5213          | 0.2195   |
| 1.6604        | 3.0   | 165  | 1.4991          | 0.2439   |
| 1.5435        | 4.0   | 220  | 1.4797          | 0.2439   |
| 1.5408        | 5.0   | 275  | 1.4620          | 0.2439   |
| 1.5878        | 6.0   | 330  | 1.4457          | 0.2683   |
| 1.4409        | 7.0   | 385  | 1.4297          | 0.2927   |
| 1.4811        | 8.0   | 440  | 1.4160          | 0.2683   |
| 1.4748        | 9.0   | 495  | 1.4030          | 0.2927   |
| 1.4898        | 10.0  | 550  | 1.3911          | 0.2927   |
| 1.4481        | 11.0  | 605  | 1.3805          | 0.3171   |
| 1.4249        | 12.0  | 660  | 1.3704          | 0.3171   |
| 1.51          | 13.0  | 715  | 1.3608          | 0.3171   |
| 1.3923        | 14.0  | 770  | 1.3525          | 0.3415   |
| 1.3961        | 15.0  | 825  | 1.3446          | 0.3415   |
| 1.4188        | 16.0  | 880  | 1.3371          | 0.3415   |
| 1.4326        | 17.0  | 935  | 1.3300          | 0.3659   |
| 1.333         | 18.0  | 990  | 1.3233          | 0.3659   |
| 1.3557        | 19.0  | 1045 | 1.3172          | 0.3659   |
| 1.3825        | 20.0  | 1100 | 1.3113          | 0.3902   |
| 1.3358        | 21.0  | 1155 | 1.3059          | 0.3902   |
| 1.3649        | 22.0  | 1210 | 1.3008          | 0.3902   |
| 1.3354        | 23.0  | 1265 | 1.2959          | 0.3902   |
| 1.3243        | 24.0  | 1320 | 1.2915          | 0.3902   |
| 1.3194        | 25.0  | 1375 | 1.2870          | 0.3902   |
| 1.3529        | 26.0  | 1430 | 1.2829          | 0.3902   |
| 1.3911        | 27.0  | 1485 | 1.2792          | 0.4146   |
| 1.2997        | 28.0  | 1540 | 1.2755          | 0.4146   |
| 1.3037        | 29.0  | 1595 | 1.2720          | 0.4146   |
| 1.3571        | 30.0  | 1650 | 1.2688          | 0.4146   |
| 1.3208        | 31.0  | 1705 | 1.2657          | 0.4146   |
| 1.325         | 32.0  | 1760 | 1.2628          | 0.4390   |
| 1.3723        | 33.0  | 1815 | 1.2602          | 0.4390   |
| 1.3195        | 34.0  | 1870 | 1.2577          | 0.4390   |
| 1.4019        | 35.0  | 1925 | 1.2554          | 0.4390   |
| 1.3831        | 36.0  | 1980 | 1.2533          | 0.4390   |
| 1.2372        | 37.0  | 2035 | 1.2514          | 0.4390   |
| 1.3729        | 38.0  | 2090 | 1.2497          | 0.4390   |
| 1.3449        | 39.0  | 2145 | 1.2481          | 0.4390   |
| 1.35          | 40.0  | 2200 | 1.2468          | 0.4390   |
| 1.3012        | 41.0  | 2255 | 1.2456          | 0.4390   |
| 1.303         | 42.0  | 2310 | 1.2445          | 0.4390   |
| 1.363         | 43.0  | 2365 | 1.2435          | 0.4390   |
| 1.3017        | 44.0  | 2420 | 1.2428          | 0.4390   |
| 1.3441        | 45.0  | 2475 | 1.2422          | 0.4390   |
| 1.3194        | 46.0  | 2530 | 1.2417          | 0.4390   |
| 1.3528        | 47.0  | 2585 | 1.2414          | 0.4390   |
| 1.3463        | 48.0  | 2640 | 1.2412          | 0.4390   |
| 1.2357        | 49.0  | 2695 | 1.2411          | 0.4390   |
| 1.3056        | 50.0  | 2750 | 1.2411          | 0.4390   |


### 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_SGD_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": 0.43902439024390244, "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