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# smids_1x_beit_base_adamax_0001_fold4

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: 1.1137
- Accuracy: 0.87

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3443        | 1.0   | 75   | 0.4137          | 0.8583   |
| 0.258         | 2.0   | 150  | 0.4036          | 0.8483   |
| 0.1343        | 3.0   | 225  | 0.4810          | 0.8533   |
| 0.0768        | 4.0   | 300  | 0.5625          | 0.86     |
| 0.0189        | 5.0   | 375  | 0.6619          | 0.8617   |
| 0.0435        | 6.0   | 450  | 0.6679          | 0.875    |
| 0.0162        | 7.0   | 525  | 0.7878          | 0.86     |
| 0.0677        | 8.0   | 600  | 0.7298          | 0.875    |
| 0.0423        | 9.0   | 675  | 0.8935          | 0.855    |
| 0.0172        | 10.0  | 750  | 0.8762          | 0.8717   |
| 0.001         | 11.0  | 825  | 0.8614          | 0.865    |
| 0.0092        | 12.0  | 900  | 0.8623          | 0.8717   |
| 0.0016        | 13.0  | 975  | 0.8916          | 0.87     |
| 0.0049        | 14.0  | 1050 | 0.8926          | 0.88     |
| 0.0101        | 15.0  | 1125 | 0.9303          | 0.8683   |
| 0.0014        | 16.0  | 1200 | 0.9140          | 0.8783   |
| 0.001         | 17.0  | 1275 | 0.9424          | 0.8817   |
| 0.0053        | 18.0  | 1350 | 0.8806          | 0.8817   |
| 0.0012        | 19.0  | 1425 | 0.9188          | 0.8917   |
| 0.0147        | 20.0  | 1500 | 0.9436          | 0.8767   |
| 0.0025        | 21.0  | 1575 | 0.9848          | 0.88     |
| 0.0092        | 22.0  | 1650 | 0.9945          | 0.8817   |
| 0.0279        | 23.0  | 1725 | 1.0063          | 0.875    |
| 0.0046        | 24.0  | 1800 | 1.0539          | 0.8767   |
| 0.0043        | 25.0  | 1875 | 1.0635          | 0.8717   |
| 0.0045        | 26.0  | 1950 | 1.0471          | 0.8733   |
| 0.0           | 27.0  | 2025 | 1.0128          | 0.8783   |
| 0.0004        | 28.0  | 2100 | 1.0296          | 0.8717   |
| 0.0001        | 29.0  | 2175 | 1.0117          | 0.875    |
| 0.0001        | 30.0  | 2250 | 1.0423          | 0.87     |
| 0.0073        | 31.0  | 2325 | 1.0722          | 0.87     |
| 0.0           | 32.0  | 2400 | 1.0662          | 0.8767   |
| 0.0           | 33.0  | 2475 | 1.0416          | 0.8717   |
| 0.0           | 34.0  | 2550 | 1.0959          | 0.8717   |
| 0.0034        | 35.0  | 2625 | 1.1220          | 0.87     |
| 0.0           | 36.0  | 2700 | 1.1441          | 0.8733   |
| 0.0           | 37.0  | 2775 | 1.1553          | 0.8733   |
| 0.0022        | 38.0  | 2850 | 1.1117          | 0.8767   |
| 0.0           | 39.0  | 2925 | 1.1002          | 0.8717   |
| 0.0           | 40.0  | 3000 | 1.1022          | 0.8683   |
| 0.003         | 41.0  | 3075 | 1.1129          | 0.8667   |
| 0.008         | 42.0  | 3150 | 1.1397          | 0.8667   |
| 0.0           | 43.0  | 3225 | 1.1224          | 0.87     |
| 0.0           | 44.0  | 3300 | 1.1186          | 0.8717   |
| 0.0           | 45.0  | 3375 | 1.1121          | 0.87     |
| 0.0001        | 46.0  | 3450 | 1.1134          | 0.87     |
| 0.0           | 47.0  | 3525 | 1.1172          | 0.8683   |
| 0.0001        | 48.0  | 3600 | 1.1134          | 0.87     |
| 0.0023        | 49.0  | 3675 | 1.1139          | 0.87     |
| 0.0022        | 50.0  | 3750 | 1.1137          | 0.87     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "smids_1x_beit_base_adamax_0001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.87, "name": "Accuracy"}]}]}]}
transformers tensorboard 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