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# HUSHEM_5x_beit_large_SGD_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: 1.2929
- Accuracy: 0.3095

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7427        | 1.0   | 55   | 1.5670          | 0.3095   |
| 1.7213        | 2.0   | 110  | 1.5438          | 0.3333   |
| 1.6062        | 3.0   | 165  | 1.5230          | 0.3333   |
| 1.579         | 4.0   | 220  | 1.5040          | 0.3333   |
| 1.6106        | 5.0   | 275  | 1.4863          | 0.3571   |
| 1.4644        | 6.0   | 330  | 1.4704          | 0.3571   |
| 1.5815        | 7.0   | 385  | 1.4564          | 0.3571   |
| 1.5985        | 8.0   | 440  | 1.4441          | 0.3333   |
| 1.5283        | 9.0   | 495  | 1.4326          | 0.3333   |
| 1.4438        | 10.0  | 550  | 1.4228          | 0.3095   |
| 1.3874        | 11.0  | 605  | 1.4136          | 0.3095   |
| 1.3958        | 12.0  | 660  | 1.4051          | 0.3095   |
| 1.4548        | 13.0  | 715  | 1.3971          | 0.3095   |
| 1.3576        | 14.0  | 770  | 1.3900          | 0.3095   |
| 1.4155        | 15.0  | 825  | 1.3829          | 0.3095   |
| 1.4576        | 16.0  | 880  | 1.3765          | 0.3095   |
| 1.5042        | 17.0  | 935  | 1.3702          | 0.3095   |
| 1.3699        | 18.0  | 990  | 1.3645          | 0.3095   |
| 1.4417        | 19.0  | 1045 | 1.3591          | 0.3095   |
| 1.4114        | 20.0  | 1100 | 1.3540          | 0.3095   |
| 1.4202        | 21.0  | 1155 | 1.3491          | 0.3095   |
| 1.4559        | 22.0  | 1210 | 1.3448          | 0.3095   |
| 1.3645        | 23.0  | 1265 | 1.3407          | 0.3095   |
| 1.3492        | 24.0  | 1320 | 1.3365          | 0.3095   |
| 1.3385        | 25.0  | 1375 | 1.3330          | 0.3095   |
| 1.4065        | 26.0  | 1430 | 1.3293          | 0.3095   |
| 1.3473        | 27.0  | 1485 | 1.3261          | 0.3095   |
| 1.382         | 28.0  | 1540 | 1.3229          | 0.3095   |
| 1.3675        | 29.0  | 1595 | 1.3200          | 0.3095   |
| 1.3494        | 30.0  | 1650 | 1.3171          | 0.3095   |
| 1.3611        | 31.0  | 1705 | 1.3145          | 0.3095   |
| 1.3791        | 32.0  | 1760 | 1.3119          | 0.3095   |
| 1.3274        | 33.0  | 1815 | 1.3096          | 0.3095   |
| 1.4571        | 34.0  | 1870 | 1.3078          | 0.3095   |
| 1.3389        | 35.0  | 1925 | 1.3057          | 0.3095   |
| 1.3757        | 36.0  | 1980 | 1.3038          | 0.3095   |
| 1.2996        | 37.0  | 2035 | 1.3021          | 0.3095   |
| 1.2811        | 38.0  | 2090 | 1.3007          | 0.3095   |
| 1.4438        | 39.0  | 2145 | 1.2993          | 0.3095   |
| 1.3301        | 40.0  | 2200 | 1.2980          | 0.3095   |
| 1.2935        | 41.0  | 2255 | 1.2969          | 0.3095   |
| 1.2576        | 42.0  | 2310 | 1.2959          | 0.3095   |
| 1.3458        | 43.0  | 2365 | 1.2950          | 0.3095   |
| 1.2816        | 44.0  | 2420 | 1.2944          | 0.3095   |
| 1.315         | 45.0  | 2475 | 1.2938          | 0.3095   |
| 1.3037        | 46.0  | 2530 | 1.2935          | 0.3095   |
| 1.3334        | 47.0  | 2585 | 1.2931          | 0.3095   |
| 1.2759        | 48.0  | 2640 | 1.2930          | 0.3095   |
| 1.3962        | 49.0  | 2695 | 1.2929          | 0.3095   |
| 1.2631        | 50.0  | 2750 | 1.2929          | 0.3095   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.30952380952380953, "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