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# SMIDS_10x_beit_base_sgd_lr001_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: 0.2568
- Accuracy: 0.9098

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5752        | 1.0   | 751   | 0.6184          | 0.7679   |
| 0.4014        | 2.0   | 1502  | 0.4581          | 0.8130   |
| 0.3169        | 3.0   | 2253  | 0.3928          | 0.8481   |
| 0.2955        | 4.0   | 3004  | 0.3566          | 0.8581   |
| 0.3383        | 5.0   | 3755  | 0.3269          | 0.8681   |
| 0.2778        | 6.0   | 4506  | 0.3112          | 0.8765   |
| 0.3166        | 7.0   | 5257  | 0.2958          | 0.8865   |
| 0.2529        | 8.0   | 6008  | 0.2917          | 0.8881   |
| 0.2765        | 9.0   | 6759  | 0.2868          | 0.8831   |
| 0.2375        | 10.0  | 7510  | 0.2807          | 0.8881   |
| 0.2745        | 11.0  | 8261  | 0.2802          | 0.8881   |
| 0.239         | 12.0  | 9012  | 0.2778          | 0.8898   |
| 0.2048        | 13.0  | 9763  | 0.2778          | 0.8881   |
| 0.1781        | 14.0  | 10514 | 0.2710          | 0.8965   |
| 0.2009        | 15.0  | 11265 | 0.2689          | 0.8948   |
| 0.189         | 16.0  | 12016 | 0.2711          | 0.8998   |
| 0.2395        | 17.0  | 12767 | 0.2694          | 0.8932   |
| 0.1965        | 18.0  | 13518 | 0.2619          | 0.8948   |
| 0.2485        | 19.0  | 14269 | 0.2629          | 0.9032   |
| 0.2141        | 20.0  | 15020 | 0.2640          | 0.8932   |
| 0.1458        | 21.0  | 15771 | 0.2669          | 0.8965   |
| 0.1624        | 22.0  | 16522 | 0.2667          | 0.8965   |
| 0.2126        | 23.0  | 17273 | 0.2669          | 0.8998   |
| 0.2025        | 24.0  | 18024 | 0.2644          | 0.9015   |
| 0.2252        | 25.0  | 18775 | 0.2609          | 0.8998   |
| 0.2251        | 26.0  | 19526 | 0.2619          | 0.8982   |
| 0.1764        | 27.0  | 20277 | 0.2636          | 0.9032   |
| 0.2368        | 28.0  | 21028 | 0.2599          | 0.9032   |
| 0.1644        | 29.0  | 21779 | 0.2586          | 0.9015   |
| 0.1587        | 30.0  | 22530 | 0.2566          | 0.9032   |
| 0.136         | 31.0  | 23281 | 0.2600          | 0.9032   |
| 0.2848        | 32.0  | 24032 | 0.2591          | 0.9048   |
| 0.2128        | 33.0  | 24783 | 0.2583          | 0.9032   |
| 0.1578        | 34.0  | 25534 | 0.2585          | 0.9048   |
| 0.2057        | 35.0  | 26285 | 0.2624          | 0.9082   |
| 0.1531        | 36.0  | 27036 | 0.2610          | 0.9048   |
| 0.2425        | 37.0  | 27787 | 0.2627          | 0.9048   |
| 0.1746        | 38.0  | 28538 | 0.2643          | 0.9115   |
| 0.0838        | 39.0  | 29289 | 0.2593          | 0.9098   |
| 0.2485        | 40.0  | 30040 | 0.2572          | 0.9082   |
| 0.1603        | 41.0  | 30791 | 0.2558          | 0.9082   |
| 0.1239        | 42.0  | 31542 | 0.2577          | 0.9065   |
| 0.1687        | 43.0  | 32293 | 0.2576          | 0.9065   |
| 0.1565        | 44.0  | 33044 | 0.2594          | 0.9098   |
| 0.1393        | 45.0  | 33795 | 0.2578          | 0.9082   |
| 0.2048        | 46.0  | 34546 | 0.2571          | 0.9082   |
| 0.1092        | 47.0  | 35297 | 0.2570          | 0.9098   |
| 0.1795        | 48.0  | 36048 | 0.2571          | 0.9098   |
| 0.1342        | 49.0  | 36799 | 0.2569          | 0.9098   |
| 0.1318        | 50.0  | 37550 | 0.2568          | 0.9098   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "SMIDS_10x_beit_base_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": 0.9098497495826378, "name": "Accuracy"}]}]}]}
transformers 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