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# SMIDS_1x_beit_large_RMSProp_lr00001_fold4

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: 1.3185
- Accuracy: 0.8867

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3268        | 1.0   | 150  | 0.4495          | 0.84     |
| 0.1858        | 2.0   | 300  | 0.5247          | 0.875    |
| 0.0799        | 3.0   | 450  | 0.5811          | 0.8633   |
| 0.0227        | 4.0   | 600  | 0.6634          | 0.8833   |
| 0.038         | 5.0   | 750  | 0.8949          | 0.8783   |
| 0.0098        | 6.0   | 900  | 0.9463          | 0.87     |
| 0.0838        | 7.0   | 1050 | 0.8774          | 0.8883   |
| 0.0634        | 8.0   | 1200 | 1.0466          | 0.8833   |
| 0.0003        | 9.0   | 1350 | 1.0509          | 0.8783   |
| 0.0032        | 10.0  | 1500 | 0.9926          | 0.88     |
| 0.0338        | 11.0  | 1650 | 0.9397          | 0.8867   |
| 0.0118        | 12.0  | 1800 | 1.1230          | 0.8667   |
| 0.047         | 13.0  | 1950 | 1.2141          | 0.8617   |
| 0.0002        | 14.0  | 2100 | 1.1828          | 0.87     |
| 0.0001        | 15.0  | 2250 | 1.3339          | 0.87     |
| 0.0           | 16.0  | 2400 | 1.2352          | 0.8717   |
| 0.0014        | 17.0  | 2550 | 1.0782          | 0.895    |
| 0.006         | 18.0  | 2700 | 1.2303          | 0.8783   |
| 0.0           | 19.0  | 2850 | 1.1239          | 0.8883   |
| 0.0143        | 20.0  | 3000 | 1.1369          | 0.8767   |
| 0.0           | 21.0  | 3150 | 1.1100          | 0.8917   |
| 0.0           | 22.0  | 3300 | 1.1362          | 0.89     |
| 0.0001        | 23.0  | 3450 | 1.3194          | 0.8817   |
| 0.0           | 24.0  | 3600 | 1.3407          | 0.88     |
| 0.0           | 25.0  | 3750 | 1.3241          | 0.8767   |
| 0.0483        | 26.0  | 3900 | 1.2271          | 0.885    |
| 0.0           | 27.0  | 4050 | 1.2326          | 0.8833   |
| 0.0           | 28.0  | 4200 | 1.2454          | 0.8867   |
| 0.0           | 29.0  | 4350 | 1.2831          | 0.8767   |
| 0.0219        | 30.0  | 4500 | 1.3413          | 0.8733   |
| 0.0           | 31.0  | 4650 | 1.3621          | 0.8817   |
| 0.0           | 32.0  | 4800 | 1.3566          | 0.8833   |
| 0.0           | 33.0  | 4950 | 1.1885          | 0.8817   |
| 0.0           | 34.0  | 5100 | 1.1661          | 0.8817   |
| 0.0098        | 35.0  | 5250 | 1.1739          | 0.8917   |
| 0.0           | 36.0  | 5400 | 1.3019          | 0.8867   |
| 0.0094        | 37.0  | 5550 | 1.2855          | 0.88     |
| 0.0           | 38.0  | 5700 | 1.3200          | 0.88     |
| 0.0085        | 39.0  | 5850 | 1.2629          | 0.8883   |
| 0.0           | 40.0  | 6000 | 1.2383          | 0.8867   |
| 0.0           | 41.0  | 6150 | 1.2541          | 0.89     |
| 0.0069        | 42.0  | 6300 | 1.2736          | 0.89     |
| 0.0           | 43.0  | 6450 | 1.2550          | 0.8867   |
| 0.0           | 44.0  | 6600 | 1.3126          | 0.8883   |
| 0.0           | 45.0  | 6750 | 1.4013          | 0.875    |
| 0.0           | 46.0  | 6900 | 1.3221          | 0.8867   |
| 0.0           | 47.0  | 7050 | 1.3221          | 0.8867   |
| 0.0           | 48.0  | 7200 | 1.3207          | 0.885    |
| 0.0           | 49.0  | 7350 | 1.3186          | 0.8867   |
| 0.0           | 50.0  | 7500 | 1.3185          | 0.8867   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8866666666666667, "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