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# smids_1x_beit_base_adamax_001_fold3

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: 1.6207
- Accuracy: 0.8067

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.961         | 1.0   | 75   | 0.9579          | 0.5083   |
| 0.8519        | 2.0   | 150  | 0.8223          | 0.555    |
| 0.8429        | 3.0   | 225  | 0.8258          | 0.5417   |
| 0.8689        | 4.0   | 300  | 1.1933          | 0.5183   |
| 0.7212        | 5.0   | 375  | 0.6887          | 0.7133   |
| 0.649         | 6.0   | 450  | 0.7128          | 0.6567   |
| 0.6409        | 7.0   | 525  | 0.6763          | 0.71     |
| 0.5869        | 8.0   | 600  | 0.5948          | 0.7383   |
| 0.5565        | 9.0   | 675  | 0.6418          | 0.695    |
| 0.5839        | 10.0  | 750  | 0.6087          | 0.7267   |
| 0.5293        | 11.0  | 825  | 0.5977          | 0.7267   |
| 0.4762        | 12.0  | 900  | 0.5491          | 0.7783   |
| 0.4499        | 13.0  | 975  | 0.5838          | 0.7517   |
| 0.4302        | 14.0  | 1050 | 0.5473          | 0.77     |
| 0.4099        | 15.0  | 1125 | 0.5508          | 0.755    |
| 0.3178        | 16.0  | 1200 | 0.5699          | 0.78     |
| 0.341         | 17.0  | 1275 | 0.6033          | 0.7933   |
| 0.2555        | 18.0  | 1350 | 0.6573          | 0.7767   |
| 0.3366        | 19.0  | 1425 | 0.5611          | 0.7933   |
| 0.1724        | 20.0  | 1500 | 0.7339          | 0.7933   |
| 0.2297        | 21.0  | 1575 | 0.8132          | 0.78     |
| 0.2293        | 22.0  | 1650 | 0.7112          | 0.7833   |
| 0.1656        | 23.0  | 1725 | 0.8681          | 0.7767   |
| 0.1488        | 24.0  | 1800 | 0.9454          | 0.79     |
| 0.1667        | 25.0  | 1875 | 0.9934          | 0.7767   |
| 0.0534        | 26.0  | 1950 | 0.9484          | 0.7767   |
| 0.1635        | 27.0  | 2025 | 1.0833          | 0.77     |
| 0.0554        | 28.0  | 2100 | 1.1552          | 0.8017   |
| 0.0938        | 29.0  | 2175 | 1.0865          | 0.7917   |
| 0.1141        | 30.0  | 2250 | 1.3605          | 0.7883   |
| 0.0561        | 31.0  | 2325 | 1.2003          | 0.8033   |
| 0.064         | 32.0  | 2400 | 1.3257          | 0.7933   |
| 0.0695        | 33.0  | 2475 | 1.6036          | 0.7883   |
| 0.0143        | 34.0  | 2550 | 1.5166          | 0.7717   |
| 0.0099        | 35.0  | 2625 | 1.5177          | 0.7833   |
| 0.046         | 36.0  | 2700 | 1.6809          | 0.7983   |
| 0.0535        | 37.0  | 2775 | 1.6548          | 0.7783   |
| 0.0142        | 38.0  | 2850 | 1.9052          | 0.7867   |
| 0.0043        | 39.0  | 2925 | 1.8855          | 0.785    |
| 0.0169        | 40.0  | 3000 | 1.8422          | 0.7983   |
| 0.0085        | 41.0  | 3075 | 1.6803          | 0.8033   |
| 0.0125        | 42.0  | 3150 | 1.4852          | 0.8033   |
| 0.0037        | 43.0  | 3225 | 1.5490          | 0.7883   |
| 0.0153        | 44.0  | 3300 | 1.3985          | 0.81     |
| 0.0066        | 45.0  | 3375 | 1.5369          | 0.8083   |
| 0.0076        | 46.0  | 3450 | 1.5177          | 0.7983   |
| 0.0089        | 47.0  | 3525 | 1.6039          | 0.7883   |
| 0.0027        | 48.0  | 3600 | 1.6013          | 0.8067   |
| 0.0003        | 49.0  | 3675 | 1.6182          | 0.8067   |
| 0.0026        | 50.0  | 3750 | 1.6207          | 0.8067   |


### 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_001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8066666666666666, "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