
<!-- 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_1x_beit_large_SGD_lr00001_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: 1.7482
- Accuracy: 0.1778

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.606         | 1.0   | 11   | 1.7650          | 0.2      |
| 1.6381        | 2.0   | 22   | 1.7642          | 0.2      |
| 1.6007        | 3.0   | 33   | 1.7634          | 0.2      |
| 1.6628        | 4.0   | 44   | 1.7626          | 0.2      |
| 1.5024        | 5.0   | 55   | 1.7618          | 0.2      |
| 1.6884        | 6.0   | 66   | 1.7611          | 0.2      |
| 1.6595        | 7.0   | 77   | 1.7604          | 0.2      |
| 1.5908        | 8.0   | 88   | 1.7598          | 0.2      |
| 1.5747        | 9.0   | 99   | 1.7592          | 0.2      |
| 1.6233        | 10.0  | 110  | 1.7585          | 0.2      |
| 1.5925        | 11.0  | 121  | 1.7579          | 0.2      |
| 1.6525        | 12.0  | 132  | 1.7573          | 0.2      |
| 1.6004        | 13.0  | 143  | 1.7566          | 0.2      |
| 1.5923        | 14.0  | 154  | 1.7561          | 0.2      |
| 1.6313        | 15.0  | 165  | 1.7556          | 0.2      |
| 1.6109        | 16.0  | 176  | 1.7551          | 0.2      |
| 1.5547        | 17.0  | 187  | 1.7546          | 0.2      |
| 1.5941        | 18.0  | 198  | 1.7541          | 0.2      |
| 1.5697        | 19.0  | 209  | 1.7537          | 0.2      |
| 1.5956        | 20.0  | 220  | 1.7533          | 0.2      |
| 1.5796        | 21.0  | 231  | 1.7529          | 0.2      |
| 1.5941        | 22.0  | 242  | 1.7525          | 0.2      |
| 1.6051        | 23.0  | 253  | 1.7521          | 0.1778   |
| 1.6121        | 24.0  | 264  | 1.7518          | 0.1778   |
| 1.5726        | 25.0  | 275  | 1.7514          | 0.1778   |
| 1.5914        | 26.0  | 286  | 1.7511          | 0.1778   |
| 1.5937        | 27.0  | 297  | 1.7508          | 0.1778   |
| 1.6399        | 28.0  | 308  | 1.7505          | 0.1778   |
| 1.5706        | 29.0  | 319  | 1.7503          | 0.1778   |
| 1.6117        | 30.0  | 330  | 1.7500          | 0.1778   |
| 1.611         | 31.0  | 341  | 1.7498          | 0.1778   |
| 1.5625        | 32.0  | 352  | 1.7495          | 0.1778   |
| 1.6273        | 33.0  | 363  | 1.7493          | 0.1778   |
| 1.5905        | 34.0  | 374  | 1.7491          | 0.1778   |
| 1.5465        | 35.0  | 385  | 1.7490          | 0.1778   |
| 1.6243        | 36.0  | 396  | 1.7488          | 0.1778   |
| 1.622         | 37.0  | 407  | 1.7487          | 0.1778   |
| 1.6884        | 38.0  | 418  | 1.7485          | 0.1778   |
| 1.5173        | 39.0  | 429  | 1.7484          | 0.1778   |
| 1.5815        | 40.0  | 440  | 1.7484          | 0.1778   |
| 1.5627        | 41.0  | 451  | 1.7483          | 0.1778   |
| 1.5847        | 42.0  | 462  | 1.7482          | 0.1778   |
| 1.6097        | 43.0  | 473  | 1.7482          | 0.1778   |
| 1.6005        | 44.0  | 484  | 1.7482          | 0.1778   |
| 1.6301        | 45.0  | 495  | 1.7482          | 0.1778   |
| 1.537         | 46.0  | 506  | 1.7482          | 0.1778   |
| 1.6543        | 47.0  | 517  | 1.7482          | 0.1778   |
| 1.5718        | 48.0  | 528  | 1.7482          | 0.1778   |
| 1.6418        | 49.0  | 539  | 1.7482          | 0.1778   |
| 1.5926        | 50.0  | 550  | 1.7482          | 0.1778   |


### 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_SGD_lr00001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.17777777777777778, "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