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# HUSHEM_5x_beit_large_RMSProp_lr0001_fold2

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: 7.4639
- Accuracy: 0.5556

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2686        | 1.0   | 54   | 1.3796          | 0.1778   |
| 1.1831        | 2.0   | 108  | 1.8502          | 0.2889   |
| 1.2509        | 3.0   | 162  | 1.4972          | 0.2889   |
| 1.0529        | 4.0   | 216  | 2.0780          | 0.2889   |
| 0.7782        | 5.0   | 270  | 2.0247          | 0.3778   |
| 0.7681        | 6.0   | 324  | 1.4900          | 0.3556   |
| 0.7233        | 7.0   | 378  | 2.8209          | 0.2667   |
| 0.7404        | 8.0   | 432  | 2.6942          | 0.3556   |
| 0.5543        | 9.0   | 486  | 2.6611          | 0.3556   |
| 0.5378        | 10.0  | 540  | 3.0719          | 0.4444   |
| 0.4979        | 11.0  | 594  | 3.0175          | 0.5333   |
| 0.5167        | 12.0  | 648  | 2.5860          | 0.4      |
| 0.6024        | 13.0  | 702  | 2.7944          | 0.3778   |
| 0.5858        | 14.0  | 756  | 2.8120          | 0.4667   |
| 0.511         | 15.0  | 810  | 3.6012          | 0.4222   |
| 0.3848        | 16.0  | 864  | 3.1476          | 0.4444   |
| 0.372         | 17.0  | 918  | 3.1682          | 0.4      |
| 0.371         | 18.0  | 972  | 3.2769          | 0.4889   |
| 0.3925        | 19.0  | 1026 | 3.3764          | 0.4667   |
| 0.4639        | 20.0  | 1080 | 3.8184          | 0.4889   |
| 0.3045        | 21.0  | 1134 | 3.9046          | 0.4667   |
| 0.2371        | 22.0  | 1188 | 4.8182          | 0.4889   |
| 0.2247        | 23.0  | 1242 | 4.5084          | 0.5778   |
| 0.3361        | 24.0  | 1296 | 3.9411          | 0.4      |
| 0.1953        | 25.0  | 1350 | 4.0684          | 0.4444   |
| 0.3355        | 26.0  | 1404 | 4.1882          | 0.4667   |
| 0.2384        | 27.0  | 1458 | 4.2151          | 0.4667   |
| 0.3623        | 28.0  | 1512 | 4.2448          | 0.5333   |
| 0.1708        | 29.0  | 1566 | 5.6362          | 0.5111   |
| 0.177         | 30.0  | 1620 | 5.4257          | 0.5778   |
| 0.1264        | 31.0  | 1674 | 5.2745          | 0.4667   |
| 0.1442        | 32.0  | 1728 | 6.0387          | 0.5778   |
| 0.0128        | 33.0  | 1782 | 6.8961          | 0.5333   |
| 0.0416        | 34.0  | 1836 | 6.2013          | 0.5556   |
| 0.1457        | 35.0  | 1890 | 6.0870          | 0.5778   |
| 0.1023        | 36.0  | 1944 | 5.7188          | 0.5333   |
| 0.174         | 37.0  | 1998 | 6.1349          | 0.5556   |
| 0.0457        | 38.0  | 2052 | 6.8055          | 0.5556   |
| 0.0914        | 39.0  | 2106 | 6.7543          | 0.6      |
| 0.036         | 40.0  | 2160 | 6.5102          | 0.5556   |
| 0.0642        | 41.0  | 2214 | 6.4098          | 0.5556   |
| 0.0           | 42.0  | 2268 | 6.1161          | 0.5778   |
| 0.0241        | 43.0  | 2322 | 6.3688          | 0.5556   |
| 0.0681        | 44.0  | 2376 | 6.9052          | 0.5778   |
| 0.0137        | 45.0  | 2430 | 7.5293          | 0.5556   |
| 0.0004        | 46.0  | 2484 | 7.4623          | 0.5556   |
| 0.0081        | 47.0  | 2538 | 7.3870          | 0.5333   |
| 0.0003        | 48.0  | 2592 | 7.4277          | 0.5556   |
| 0.0096        | 49.0  | 2646 | 7.4638          | 0.5556   |
| 0.0072        | 50.0  | 2700 | 7.4639          | 0.5556   |


### 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_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5555555555555556, "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