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# HUSHEM_1x_beit_large_RMSProp_lr0001_fold1

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: 5.9249
- Accuracy: 0.4444

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8671        | 1.0   | 11   | 1.4048          | 0.2444   |
| 1.4492        | 2.0   | 22   | 1.4036          | 0.2444   |
| 1.4054        | 3.0   | 33   | 1.4276          | 0.2444   |
| 1.388         | 4.0   | 44   | 1.4102          | 0.2444   |
| 1.3616        | 5.0   | 55   | 2.0488          | 0.2444   |
| 1.2567        | 6.0   | 66   | 1.6519          | 0.2667   |
| 1.2829        | 7.0   | 77   | 1.8761          | 0.3111   |
| 1.0586        | 8.0   | 88   | 1.3454          | 0.4      |
| 1.1068        | 9.0   | 99   | 1.9967          | 0.3556   |
| 0.8609        | 10.0  | 110  | 2.0334          | 0.4      |
| 0.7563        | 11.0  | 121  | 1.7392          | 0.4      |
| 0.8003        | 12.0  | 132  | 1.7436          | 0.4      |
| 0.69          | 13.0  | 143  | 1.3597          | 0.4      |
| 0.8412        | 14.0  | 154  | 2.0998          | 0.3778   |
| 0.5882        | 15.0  | 165  | 1.4075          | 0.4      |
| 0.6452        | 16.0  | 176  | 2.3025          | 0.4      |
| 0.5843        | 17.0  | 187  | 1.2765          | 0.4222   |
| 0.5034        | 18.0  | 198  | 1.7532          | 0.4222   |
| 0.6343        | 19.0  | 209  | 1.4334          | 0.4444   |
| 0.4836        | 20.0  | 220  | 3.0203          | 0.4      |
| 0.4188        | 21.0  | 231  | 1.8023          | 0.4889   |
| 0.3871        | 22.0  | 242  | 1.8028          | 0.4667   |
| 0.3546        | 23.0  | 253  | 3.3692          | 0.4222   |
| 0.323         | 24.0  | 264  | 2.2128          | 0.5111   |
| 0.2646        | 25.0  | 275  | 2.9418          | 0.4889   |
| 0.2497        | 26.0  | 286  | 3.4479          | 0.4667   |
| 0.2556        | 27.0  | 297  | 4.0654          | 0.4444   |
| 0.1852        | 28.0  | 308  | 3.4657          | 0.5111   |
| 0.1598        | 29.0  | 319  | 3.8551          | 0.5111   |
| 0.1509        | 30.0  | 330  | 2.6108          | 0.6444   |
| 0.0835        | 31.0  | 341  | 6.1594          | 0.4444   |
| 0.0662        | 32.0  | 352  | 5.1735          | 0.4222   |
| 0.1776        | 33.0  | 363  | 4.9623          | 0.4667   |
| 0.0315        | 34.0  | 374  | 4.9846          | 0.4667   |
| 0.084         | 35.0  | 385  | 6.1439          | 0.4444   |
| 0.0028        | 36.0  | 396  | 5.5514          | 0.4444   |
| 0.0258        | 37.0  | 407  | 5.9576          | 0.4      |
| 0.0486        | 38.0  | 418  | 4.7554          | 0.3778   |
| 0.0767        | 39.0  | 429  | 5.7575          | 0.4444   |
| 0.0226        | 40.0  | 440  | 7.0096          | 0.4222   |
| 0.2828        | 41.0  | 451  | 5.2026          | 0.4667   |
| 0.0003        | 42.0  | 462  | 6.3065          | 0.4222   |
| 0.0273        | 43.0  | 473  | 7.0141          | 0.4222   |
| 0.0962        | 44.0  | 484  | 5.9962          | 0.4444   |
| 0.0782        | 45.0  | 495  | 5.9214          | 0.4444   |
| 0.0083        | 46.0  | 506  | 5.9249          | 0.4444   |
| 0.0041        | 47.0  | 517  | 5.9249          | 0.4444   |
| 0.0036        | 48.0  | 528  | 5.9249          | 0.4444   |
| 0.0094        | 49.0  | 539  | 5.9249          | 0.4444   |
| 0.0052        | 50.0  | 550  | 5.9249          | 0.4444   |


### 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_1x_beit_large_RMSProp_lr0001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.4444444444444444, "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