
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# HUSHEM_5x_beit_large_SGDx_lr00001_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: 1.5374
- Accuracy: 0.3333

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7645        | 1.0   | 55   | 1.5899          | 0.3333   |
| 1.7769        | 2.0   | 110  | 1.5874          | 0.3333   |
| 1.6613        | 3.0   | 165  | 1.5850          | 0.3095   |
| 1.6666        | 4.0   | 220  | 1.5827          | 0.3095   |
| 1.7325        | 5.0   | 275  | 1.5804          | 0.3095   |
| 1.5986        | 6.0   | 330  | 1.5781          | 0.3095   |
| 1.6932        | 7.0   | 385  | 1.5760          | 0.3095   |
| 1.7656        | 8.0   | 440  | 1.5740          | 0.3095   |
| 1.6927        | 9.0   | 495  | 1.5721          | 0.3095   |
| 1.5921        | 10.0  | 550  | 1.5702          | 0.3095   |
| 1.5352        | 11.0  | 605  | 1.5684          | 0.3095   |
| 1.547         | 12.0  | 660  | 1.5666          | 0.3095   |
| 1.673         | 13.0  | 715  | 1.5649          | 0.3095   |
| 1.4727        | 14.0  | 770  | 1.5633          | 0.3095   |
| 1.5971        | 15.0  | 825  | 1.5617          | 0.3095   |
| 1.7391        | 16.0  | 880  | 1.5602          | 0.3095   |
| 1.7611        | 17.0  | 935  | 1.5588          | 0.3095   |
| 1.6172        | 18.0  | 990  | 1.5574          | 0.3095   |
| 1.6927        | 19.0  | 1045 | 1.5560          | 0.3095   |
| 1.698         | 20.0  | 1100 | 1.5547          | 0.3333   |
| 1.6347        | 21.0  | 1155 | 1.5535          | 0.3333   |
| 1.7555        | 22.0  | 1210 | 1.5523          | 0.3333   |
| 1.6           | 23.0  | 1265 | 1.5511          | 0.3333   |
| 1.5336        | 24.0  | 1320 | 1.5500          | 0.3333   |
| 1.5963        | 25.0  | 1375 | 1.5490          | 0.3333   |
| 1.6651        | 26.0  | 1430 | 1.5480          | 0.3333   |
| 1.6625        | 27.0  | 1485 | 1.5470          | 0.3333   |
| 1.6463        | 28.0  | 1540 | 1.5461          | 0.3333   |
| 1.5874        | 29.0  | 1595 | 1.5453          | 0.3333   |
| 1.6703        | 30.0  | 1650 | 1.5445          | 0.3333   |
| 1.6781        | 31.0  | 1705 | 1.5437          | 0.3333   |
| 1.6541        | 32.0  | 1760 | 1.5430          | 0.3333   |
| 1.5296        | 33.0  | 1815 | 1.5423          | 0.3333   |
| 1.7048        | 34.0  | 1870 | 1.5417          | 0.3333   |
| 1.622         | 35.0  | 1925 | 1.5411          | 0.3333   |
| 1.6377        | 36.0  | 1980 | 1.5405          | 0.3333   |
| 1.5452        | 37.0  | 2035 | 1.5401          | 0.3333   |
| 1.5482        | 38.0  | 2090 | 1.5396          | 0.3333   |
| 1.7874        | 39.0  | 2145 | 1.5392          | 0.3333   |
| 1.6496        | 40.0  | 2200 | 1.5389          | 0.3333   |
| 1.6009        | 41.0  | 2255 | 1.5386          | 0.3333   |
| 1.5627        | 42.0  | 2310 | 1.5383          | 0.3333   |
| 1.663         | 43.0  | 2365 | 1.5380          | 0.3333   |
| 1.5604        | 44.0  | 2420 | 1.5378          | 0.3333   |
| 1.652         | 45.0  | 2475 | 1.5377          | 0.3333   |
| 1.5633        | 46.0  | 2530 | 1.5376          | 0.3333   |
| 1.6026        | 47.0  | 2585 | 1.5375          | 0.3333   |
| 1.5778        | 48.0  | 2640 | 1.5374          | 0.3333   |
| 1.711         | 49.0  | 2695 | 1.5374          | 0.3333   |
| 1.5326        | 50.0  | 2750 | 1.5374          | 0.3333   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"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_SGDx_lr00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.3333333333333333, "name": "Accuracy"}]}]}]}
transformers safetensors 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