
<!-- 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_10x_beit_large_SGD_lr001_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: 0.4507
- Accuracy: 0.8222

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2909        | 1.0   | 107  | 1.3364          | 0.4      |
| 1.0845        | 2.0   | 214  | 1.2793          | 0.3778   |
| 1.0188        | 3.0   | 321  | 1.2259          | 0.4222   |
| 0.8598        | 4.0   | 428  | 1.1737          | 0.4667   |
| 0.7075        | 5.0   | 535  | 1.1131          | 0.5111   |
| 0.6698        | 6.0   | 642  | 1.0581          | 0.5556   |
| 0.6303        | 7.0   | 749  | 0.9915          | 0.5333   |
| 0.5629        | 8.0   | 856  | 0.9533          | 0.6      |
| 0.5337        | 9.0   | 963  | 0.8941          | 0.6444   |
| 0.4171        | 10.0  | 1070 | 0.8642          | 0.6667   |
| 0.4307        | 11.0  | 1177 | 0.8190          | 0.7111   |
| 0.3105        | 12.0  | 1284 | 0.7969          | 0.7333   |
| 0.3408        | 13.0  | 1391 | 0.7564          | 0.7111   |
| 0.3587        | 14.0  | 1498 | 0.7257          | 0.7111   |
| 0.2968        | 15.0  | 1605 | 0.7105          | 0.7333   |
| 0.253         | 16.0  | 1712 | 0.6907          | 0.7111   |
| 0.2724        | 17.0  | 1819 | 0.6636          | 0.7111   |
| 0.2326        | 18.0  | 1926 | 0.6383          | 0.7778   |
| 0.258         | 19.0  | 2033 | 0.6279          | 0.8      |
| 0.1524        | 20.0  | 2140 | 0.6101          | 0.7778   |
| 0.174         | 21.0  | 2247 | 0.5992          | 0.8      |
| 0.1868        | 22.0  | 2354 | 0.5814          | 0.8      |
| 0.1717        | 23.0  | 2461 | 0.5755          | 0.7778   |
| 0.1574        | 24.0  | 2568 | 0.5649          | 0.8      |
| 0.1252        | 25.0  | 2675 | 0.5540          | 0.7778   |
| 0.1415        | 26.0  | 2782 | 0.5434          | 0.7556   |
| 0.1004        | 27.0  | 2889 | 0.5345          | 0.7556   |
| 0.1268        | 28.0  | 2996 | 0.5266          | 0.7778   |
| 0.1377        | 29.0  | 3103 | 0.5166          | 0.7778   |
| 0.1296        | 30.0  | 3210 | 0.5101          | 0.8      |
| 0.1113        | 31.0  | 3317 | 0.5025          | 0.7778   |
| 0.124         | 32.0  | 3424 | 0.4951          | 0.8      |
| 0.1431        | 33.0  | 3531 | 0.4939          | 0.8      |
| 0.125         | 34.0  | 3638 | 0.4881          | 0.8222   |
| 0.1115        | 35.0  | 3745 | 0.4810          | 0.8222   |
| 0.11          | 36.0  | 3852 | 0.4777          | 0.8222   |
| 0.0885        | 37.0  | 3959 | 0.4711          | 0.8222   |
| 0.0911        | 38.0  | 4066 | 0.4669          | 0.8222   |
| 0.1005        | 39.0  | 4173 | 0.4618          | 0.8222   |
| 0.0899        | 40.0  | 4280 | 0.4623          | 0.8222   |
| 0.0809        | 41.0  | 4387 | 0.4600          | 0.8222   |
| 0.0993        | 42.0  | 4494 | 0.4583          | 0.8222   |
| 0.0913        | 43.0  | 4601 | 0.4551          | 0.8222   |
| 0.0811        | 44.0  | 4708 | 0.4542          | 0.8222   |
| 0.0953        | 45.0  | 4815 | 0.4539          | 0.8222   |
| 0.0877        | 46.0  | 4922 | 0.4518          | 0.8222   |
| 0.0993        | 47.0  | 5029 | 0.4510          | 0.8222   |
| 0.0906        | 48.0  | 5136 | 0.4507          | 0.8222   |
| 0.0744        | 49.0  | 5243 | 0.4507          | 0.8222   |
| 0.0766        | 50.0  | 5350 | 0.4507          | 0.8222   |


### 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_10x_beit_large_SGD_lr001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8222222222222222, "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