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# SMIDS_1x_beit_large_SGD_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: 0.5256
- Accuracy: 0.8053

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5621        | 1.0   | 150  | 1.4443          | 0.2812   |
| 1.2622        | 2.0   | 300  | 1.2499          | 0.3344   |
| 1.1597        | 3.0   | 450  | 1.1175          | 0.4060   |
| 1.0952        | 4.0   | 600  | 1.0281          | 0.5008   |
| 0.9632        | 5.0   | 750  | 0.9620          | 0.5557   |
| 0.9483        | 6.0   | 900  | 0.9139          | 0.5857   |
| 0.9386        | 7.0   | 1050 | 0.8764          | 0.6256   |
| 0.8981        | 8.0   | 1200 | 0.8447          | 0.6456   |
| 0.83          | 9.0   | 1350 | 0.8174          | 0.6539   |
| 0.8248        | 10.0  | 1500 | 0.7928          | 0.6672   |
| 0.8091        | 11.0  | 1650 | 0.7713          | 0.6755   |
| 0.8712        | 12.0  | 1800 | 0.7515          | 0.6922   |
| 0.7897        | 13.0  | 1950 | 0.7333          | 0.7038   |
| 0.8354        | 14.0  | 2100 | 0.7167          | 0.7088   |
| 0.7125        | 15.0  | 2250 | 0.7012          | 0.7155   |
| 0.7275        | 16.0  | 2400 | 0.6870          | 0.7271   |
| 0.7474        | 17.0  | 2550 | 0.6738          | 0.7321   |
| 0.6976        | 18.0  | 2700 | 0.6617          | 0.7354   |
| 0.6107        | 19.0  | 2850 | 0.6502          | 0.7388   |
| 0.6746        | 20.0  | 3000 | 0.6395          | 0.7404   |
| 0.7248        | 21.0  | 3150 | 0.6295          | 0.7471   |
| 0.6428        | 22.0  | 3300 | 0.6204          | 0.7537   |
| 0.6393        | 23.0  | 3450 | 0.6121          | 0.7554   |
| 0.6726        | 24.0  | 3600 | 0.6043          | 0.7604   |
| 0.583         | 25.0  | 3750 | 0.5971          | 0.7654   |
| 0.5735        | 26.0  | 3900 | 0.5903          | 0.7704   |
| 0.6008        | 27.0  | 4050 | 0.5840          | 0.7704   |
| 0.5618        | 28.0  | 4200 | 0.5781          | 0.7720   |
| 0.5777        | 29.0  | 4350 | 0.5725          | 0.7754   |
| 0.6299        | 30.0  | 4500 | 0.5675          | 0.7804   |
| 0.6117        | 31.0  | 4650 | 0.5627          | 0.7820   |
| 0.6188        | 32.0  | 4800 | 0.5585          | 0.7820   |
| 0.598         | 33.0  | 4950 | 0.5544          | 0.7870   |
| 0.6143        | 34.0  | 5100 | 0.5508          | 0.7870   |
| 0.6175        | 35.0  | 5250 | 0.5474          | 0.7887   |
| 0.5782        | 36.0  | 5400 | 0.5442          | 0.7920   |
| 0.62          | 37.0  | 5550 | 0.5414          | 0.7970   |
| 0.5379        | 38.0  | 5700 | 0.5388          | 0.8003   |
| 0.6229        | 39.0  | 5850 | 0.5365          | 0.8037   |
| 0.5617        | 40.0  | 6000 | 0.5343          | 0.8053   |
| 0.5602        | 41.0  | 6150 | 0.5325          | 0.8053   |
| 0.5665        | 42.0  | 6300 | 0.5309          | 0.8053   |
| 0.6283        | 43.0  | 6450 | 0.5295          | 0.8053   |
| 0.5709        | 44.0  | 6600 | 0.5284          | 0.8053   |
| 0.5791        | 45.0  | 6750 | 0.5274          | 0.8053   |
| 0.5919        | 46.0  | 6900 | 0.5267          | 0.8053   |
| 0.5716        | 47.0  | 7050 | 0.5262          | 0.8053   |
| 0.5659        | 48.0  | 7200 | 0.5258          | 0.8053   |
| 0.585         | 49.0  | 7350 | 0.5256          | 0.8053   |
| 0.6058        | 50.0  | 7500 | 0.5256          | 0.8053   |


### 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": "SMIDS_1x_beit_large_SGD_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": 0.8053244592346089, "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