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# SMIDS_1x_beit_large_SGD_lr00001_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: 1.2554
- Accuracy: 0.3289

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4891        | 1.0   | 151  | 1.5399          | 0.2621   |
| 1.4559        | 2.0   | 302  | 1.5243          | 0.2638   |
| 1.4508        | 3.0   | 453  | 1.5095          | 0.2638   |
| 1.3941        | 4.0   | 604  | 1.4952          | 0.2654   |
| 1.443         | 5.0   | 755  | 1.4816          | 0.2638   |
| 1.3588        | 6.0   | 906  | 1.4686          | 0.2654   |
| 1.4973        | 7.0   | 1057 | 1.4562          | 0.2654   |
| 1.4012        | 8.0   | 1208 | 1.4442          | 0.2688   |
| 1.4246        | 9.0   | 1359 | 1.4330          | 0.2688   |
| 1.3326        | 10.0  | 1510 | 1.4222          | 0.2721   |
| 1.3773        | 11.0  | 1661 | 1.4118          | 0.2738   |
| 1.4048        | 12.0  | 1812 | 1.4018          | 0.2788   |
| 1.3156        | 13.0  | 1963 | 1.3924          | 0.2738   |
| 1.3176        | 14.0  | 2114 | 1.3832          | 0.2755   |
| 1.3482        | 15.0  | 2265 | 1.3746          | 0.2771   |
| 1.2942        | 16.0  | 2416 | 1.3663          | 0.2788   |
| 1.3412        | 17.0  | 2567 | 1.3586          | 0.2838   |
| 1.3905        | 18.0  | 2718 | 1.3511          | 0.2871   |
| 1.3165        | 19.0  | 2869 | 1.3442          | 0.2871   |
| 1.371         | 20.0  | 3020 | 1.3376          | 0.2888   |
| 1.2321        | 21.0  | 3171 | 1.3312          | 0.2905   |
| 1.3331        | 22.0  | 3322 | 1.3251          | 0.2922   |
| 1.2074        | 23.0  | 3473 | 1.3194          | 0.2938   |
| 1.3596        | 24.0  | 3624 | 1.3140          | 0.2972   |
| 1.2383        | 25.0  | 3775 | 1.3089          | 0.2988   |
| 1.2201        | 26.0  | 3926 | 1.3041          | 0.3022   |
| 1.1344        | 27.0  | 4077 | 1.2996          | 0.3055   |
| 1.237         | 28.0  | 4228 | 1.2953          | 0.3105   |
| 1.2121        | 29.0  | 4379 | 1.2913          | 0.3105   |
| 1.1733        | 30.0  | 4530 | 1.2876          | 0.3105   |
| 1.3018        | 31.0  | 4681 | 1.2841          | 0.3122   |
| 1.2657        | 32.0  | 4832 | 1.2808          | 0.3139   |
| 1.231         | 33.0  | 4983 | 1.2777          | 0.3139   |
| 1.262         | 34.0  | 5134 | 1.2749          | 0.3155   |
| 1.2035        | 35.0  | 5285 | 1.2723          | 0.3155   |
| 1.184         | 36.0  | 5436 | 1.2699          | 0.3189   |
| 1.2232        | 37.0  | 5587 | 1.2677          | 0.3205   |
| 1.2558        | 38.0  | 5738 | 1.2657          | 0.3222   |
| 1.1654        | 39.0  | 5889 | 1.2639          | 0.3272   |
| 1.3348        | 40.0  | 6040 | 1.2623          | 0.3272   |
| 1.2712        | 41.0  | 6191 | 1.2608          | 0.3272   |
| 1.2662        | 42.0  | 6342 | 1.2595          | 0.3272   |
| 1.1472        | 43.0  | 6493 | 1.2585          | 0.3272   |
| 1.2323        | 44.0  | 6644 | 1.2575          | 0.3272   |
| 1.2402        | 45.0  | 6795 | 1.2568          | 0.3272   |
| 1.2095        | 46.0  | 6946 | 1.2562          | 0.3272   |
| 1.1604        | 47.0  | 7097 | 1.2558          | 0.3272   |
| 1.3185        | 48.0  | 7248 | 1.2556          | 0.3289   |
| 1.1621        | 49.0  | 7399 | 1.2554          | 0.3289   |
| 1.1776        | 50.0  | 7550 | 1.2554          | 0.3289   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.328881469115192, "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