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# SMIDS_1x_beit_large_RMSProp_lr00001_fold5

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: 1.0944
- Accuracy: 0.8967

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2591        | 1.0   | 150  | 0.3427          | 0.8733   |
| 0.1839        | 2.0   | 300  | 0.2827          | 0.885    |
| 0.1697        | 3.0   | 450  | 0.3869          | 0.8883   |
| 0.0166        | 4.0   | 600  | 0.5167          | 0.8983   |
| 0.0312        | 5.0   | 750  | 0.6421          | 0.8867   |
| 0.0009        | 6.0   | 900  | 0.6738          | 0.9033   |
| 0.0089        | 7.0   | 1050 | 0.8762          | 0.885    |
| 0.0359        | 8.0   | 1200 | 0.7820          | 0.8833   |
| 0.052         | 9.0   | 1350 | 0.6930          | 0.8833   |
| 0.0           | 10.0  | 1500 | 0.7956          | 0.885    |
| 0.0289        | 11.0  | 1650 | 0.6899          | 0.905    |
| 0.0215        | 12.0  | 1800 | 0.9536          | 0.875    |
| 0.0226        | 13.0  | 1950 | 0.7811          | 0.8917   |
| 0.0           | 14.0  | 2100 | 0.9852          | 0.895    |
| 0.0001        | 15.0  | 2250 | 0.8485          | 0.9017   |
| 0.0027        | 16.0  | 2400 | 0.8245          | 0.9033   |
| 0.0           | 17.0  | 2550 | 0.9083          | 0.89     |
| 0.0118        | 18.0  | 2700 | 0.9937          | 0.9083   |
| 0.0           | 19.0  | 2850 | 1.0026          | 0.8933   |
| 0.0           | 20.0  | 3000 | 0.9988          | 0.8883   |
| 0.0           | 21.0  | 3150 | 0.9399          | 0.8983   |
| 0.0796        | 22.0  | 3300 | 0.9764          | 0.9067   |
| 0.0           | 23.0  | 3450 | 1.0362          | 0.8917   |
| 0.0           | 24.0  | 3600 | 1.0633          | 0.8917   |
| 0.0001        | 25.0  | 3750 | 1.0854          | 0.8933   |
| 0.0226        | 26.0  | 3900 | 1.2232          | 0.8867   |
| 0.0           | 27.0  | 4050 | 1.1265          | 0.9017   |
| 0.0173        | 28.0  | 4200 | 0.9992          | 0.9083   |
| 0.0039        | 29.0  | 4350 | 1.0141          | 0.9033   |
| 0.0316        | 30.0  | 4500 | 1.2049          | 0.8833   |
| 0.0047        | 31.0  | 4650 | 1.1012          | 0.8967   |
| 0.0           | 32.0  | 4800 | 1.0713          | 0.8983   |
| 0.0199        | 33.0  | 4950 | 1.0854          | 0.8983   |
| 0.0048        | 34.0  | 5100 | 1.0560          | 0.9017   |
| 0.0           | 35.0  | 5250 | 1.1222          | 0.9      |
| 0.0           | 36.0  | 5400 | 1.1315          | 0.8983   |
| 0.0           | 37.0  | 5550 | 1.1177          | 0.9017   |
| 0.0088        | 38.0  | 5700 | 1.0922          | 0.905    |
| 0.015         | 39.0  | 5850 | 1.0729          | 0.9117   |
| 0.0           | 40.0  | 6000 | 1.0107          | 0.91     |
| 0.0012        | 41.0  | 6150 | 1.0920          | 0.905    |
| 0.0042        | 42.0  | 6300 | 1.0895          | 0.8967   |
| 0.0058        | 43.0  | 6450 | 1.1104          | 0.895    |
| 0.0           | 44.0  | 6600 | 1.0591          | 0.9033   |
| 0.0           | 45.0  | 6750 | 1.1046          | 0.8967   |
| 0.0073        | 46.0  | 6900 | 1.1212          | 0.895    |
| 0.0           | 47.0  | 7050 | 1.1236          | 0.8967   |
| 0.0           | 48.0  | 7200 | 1.0937          | 0.8967   |
| 0.0111        | 49.0  | 7350 | 1.0931          | 0.8967   |
| 0.0           | 50.0  | 7500 | 1.0944          | 0.8967   |


### 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_RMSProp_lr00001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8966666666666666, "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