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# SMIDS_1x_beit_large_SGD_lr00001_fold4

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: 1.2241
- Accuracy: 0.355

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6389        | 1.0   | 150  | 1.7053          | 0.2933   |
| 1.7093        | 2.0   | 300  | 1.6786          | 0.2933   |
| 1.5164        | 3.0   | 450  | 1.6531          | 0.295    |
| 1.5839        | 4.0   | 600  | 1.6290          | 0.2967   |
| 1.4954        | 5.0   | 750  | 1.6055          | 0.2933   |
| 1.5416        | 6.0   | 900  | 1.5834          | 0.2967   |
| 1.4894        | 7.0   | 1050 | 1.5620          | 0.2983   |
| 1.5454        | 8.0   | 1200 | 1.5419          | 0.3      |
| 1.4541        | 9.0   | 1350 | 1.5225          | 0.2983   |
| 1.3917        | 10.0  | 1500 | 1.5039          | 0.295    |
| 1.519         | 11.0  | 1650 | 1.4864          | 0.2933   |
| 1.4518        | 12.0  | 1800 | 1.4695          | 0.295    |
| 1.458         | 13.0  | 1950 | 1.4533          | 0.3      |
| 1.3786        | 14.0  | 2100 | 1.4380          | 0.3      |
| 1.2826        | 15.0  | 2250 | 1.4234          | 0.3      |
| 1.3926        | 16.0  | 2400 | 1.4093          | 0.3017   |
| 1.4638        | 17.0  | 2550 | 1.3961          | 0.3017   |
| 1.4064        | 18.0  | 2700 | 1.3835          | 0.3      |
| 1.3165        | 19.0  | 2850 | 1.3718          | 0.3017   |
| 1.3183        | 20.0  | 3000 | 1.3605          | 0.3033   |
| 1.3559        | 21.0  | 3150 | 1.3498          | 0.31     |
| 1.3874        | 22.0  | 3300 | 1.3396          | 0.31     |
| 1.3565        | 23.0  | 3450 | 1.3302          | 0.3117   |
| 1.2954        | 24.0  | 3600 | 1.3212          | 0.3133   |
| 1.3216        | 25.0  | 3750 | 1.3127          | 0.3183   |
| 1.3645        | 26.0  | 3900 | 1.3047          | 0.3217   |
| 1.2951        | 27.0  | 4050 | 1.2972          | 0.325    |
| 1.3124        | 28.0  | 4200 | 1.2901          | 0.325    |
| 1.2115        | 29.0  | 4350 | 1.2835          | 0.325    |
| 1.2815        | 30.0  | 4500 | 1.2773          | 0.3267   |
| 1.2143        | 31.0  | 4650 | 1.2715          | 0.3267   |
| 1.2637        | 32.0  | 4800 | 1.2661          | 0.3267   |
| 1.1974        | 33.0  | 4950 | 1.2610          | 0.3267   |
| 1.2541        | 34.0  | 5100 | 1.2564          | 0.3283   |
| 1.2021        | 35.0  | 5250 | 1.2521          | 0.3283   |
| 1.2589        | 36.0  | 5400 | 1.2481          | 0.33     |
| 1.2461        | 37.0  | 5550 | 1.2445          | 0.3367   |
| 1.255         | 38.0  | 5700 | 1.2413          | 0.34     |
| 1.2563        | 39.0  | 5850 | 1.2383          | 0.345    |
| 1.2891        | 40.0  | 6000 | 1.2357          | 0.345    |
| 1.2387        | 41.0  | 6150 | 1.2333          | 0.3467   |
| 1.2496        | 42.0  | 6300 | 1.2312          | 0.345    |
| 1.2277        | 43.0  | 6450 | 1.2295          | 0.345    |
| 1.2598        | 44.0  | 6600 | 1.2280          | 0.345    |
| 1.2242        | 45.0  | 6750 | 1.2267          | 0.3483   |
| 1.2808        | 46.0  | 6900 | 1.2257          | 0.35     |
| 1.2529        | 47.0  | 7050 | 1.2250          | 0.355    |
| 1.214         | 48.0  | 7200 | 1.2245          | 0.355    |
| 1.238         | 49.0  | 7350 | 1.2242          | 0.355    |
| 1.2133        | 50.0  | 7500 | 1.2241          | 0.355    |


### 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_lr00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.355, "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