
<!-- 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_base_rms_001_fold1

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2430
- 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5782        | 1.0   | 27   | 1.4061          | 0.2444   |
| 1.4004        | 2.0   | 54   | 1.4559          | 0.2444   |
| 1.3873        | 3.0   | 81   | 1.4120          | 0.2444   |
| 1.3666        | 4.0   | 108  | 1.6275          | 0.2444   |
| 1.3597        | 5.0   | 135  | 1.4398          | 0.2444   |
| 1.2814        | 6.0   | 162  | 1.5328          | 0.2444   |
| 1.2056        | 7.0   | 189  | 1.5389          | 0.2      |
| 1.1635        | 8.0   | 216  | 1.5332          | 0.2444   |
| 1.1235        | 9.0   | 243  | 1.6681          | 0.2444   |
| 1.1484        | 10.0  | 270  | 1.6176          | 0.2667   |
| 1.1757        | 11.0  | 297  | 1.6312          | 0.2444   |
| 1.1297        | 12.0  | 324  | 1.5067          | 0.2444   |
| 1.1448        | 13.0  | 351  | 1.5657          | 0.2444   |
| 1.1725        | 14.0  | 378  | 1.5184          | 0.1556   |
| 1.1591        | 15.0  | 405  | 1.5790          | 0.2444   |
| 1.1549        | 16.0  | 432  | 1.5501          | 0.2444   |
| 1.0865        | 17.0  | 459  | 1.5776          | 0.2444   |
| 1.1351        | 18.0  | 486  | 1.6195          | 0.3111   |
| 1.0974        | 19.0  | 513  | 1.5360          | 0.2444   |
| 1.0992        | 20.0  | 540  | 1.5742          | 0.3111   |
| 1.0894        | 21.0  | 567  | 1.4918          | 0.3778   |
| 1.0557        | 22.0  | 594  | 1.5742          | 0.2444   |
| 1.0574        | 23.0  | 621  | 1.5043          | 0.4222   |
| 1.0148        | 24.0  | 648  | 1.3535          | 0.4222   |
| 1.1133        | 25.0  | 675  | 1.4897          | 0.4      |
| 1.02          | 26.0  | 702  | 1.4554          | 0.4222   |
| 1.0107        | 27.0  | 729  | 1.4238          | 0.4      |
| 0.9307        | 28.0  | 756  | 1.7644          | 0.3556   |
| 0.8335        | 29.0  | 783  | 2.0253          | 0.3556   |
| 0.8203        | 30.0  | 810  | 1.7990          | 0.3556   |
| 0.7263        | 31.0  | 837  | 1.6909          | 0.3778   |
| 0.8387        | 32.0  | 864  | 1.4758          | 0.4      |
| 0.6837        | 33.0  | 891  | 2.1584          | 0.3556   |
| 0.7155        | 34.0  | 918  | 1.7102          | 0.3778   |
| 0.6349        | 35.0  | 945  | 1.1875          | 0.4667   |
| 0.6331        | 36.0  | 972  | 1.9965          | 0.4222   |
| 0.5871        | 37.0  | 999  | 1.7881          | 0.4      |
| 0.595         | 38.0  | 1026 | 1.7629          | 0.4      |
| 0.5266        | 39.0  | 1053 | 1.6720          | 0.4222   |
| 0.4985        | 40.0  | 1080 | 2.3229          | 0.4222   |
| 0.4855        | 41.0  | 1107 | 1.6470          | 0.4444   |
| 0.503         | 42.0  | 1134 | 1.7515          | 0.4667   |
| 0.4432        | 43.0  | 1161 | 2.0538          | 0.4222   |
| 0.3668        | 44.0  | 1188 | 2.1471          | 0.4444   |
| 0.3654        | 45.0  | 1215 | 2.0004          | 0.4444   |
| 0.3317        | 46.0  | 1242 | 2.1973          | 0.4444   |
| 0.2413        | 47.0  | 1269 | 2.2882          | 0.4444   |
| 0.2395        | 48.0  | 1296 | 2.2389          | 0.4444   |
| 0.2502        | 49.0  | 1323 | 2.2430          | 0.4444   |
| 0.237         | 50.0  | 1350 | 2.2430          | 0.4444   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "hushem_5x_beit_base_rms_001_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 tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us