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# SMIDS_1x_beit_large_RMSProp_lr0001_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: 1.6725
- Accuracy: 0.8233

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8872        | 1.0   | 150  | 0.7967          | 0.5717   |
| 0.7763        | 2.0   | 300  | 0.7037          | 0.7333   |
| 0.7349        | 3.0   | 450  | 0.6964          | 0.6833   |
| 0.6956        | 4.0   | 600  | 0.6259          | 0.715    |
| 0.5904        | 5.0   | 750  | 0.4976          | 0.7967   |
| 0.4235        | 6.0   | 900  | 0.6113          | 0.7883   |
| 0.4611        | 7.0   | 1050 | 0.4661          | 0.82     |
| 0.5293        | 8.0   | 1200 | 0.4971          | 0.7783   |
| 0.352         | 9.0   | 1350 | 0.7733          | 0.7317   |
| 0.4018        | 10.0  | 1500 | 0.5345          | 0.795    |
| 0.3956        | 11.0  | 1650 | 0.5867          | 0.82     |
| 0.3397        | 12.0  | 1800 | 0.5179          | 0.8133   |
| 0.1896        | 13.0  | 1950 | 0.6920          | 0.8017   |
| 0.0625        | 14.0  | 2100 | 0.9640          | 0.7917   |
| 0.1623        | 15.0  | 2250 | 0.8866          | 0.7983   |
| 0.1436        | 16.0  | 2400 | 1.0043          | 0.7933   |
| 0.0648        | 17.0  | 2550 | 0.8933          | 0.795    |
| 0.2113        | 18.0  | 2700 | 0.7938          | 0.795    |
| 0.1579        | 19.0  | 2850 | 1.2080          | 0.785    |
| 0.0603        | 20.0  | 3000 | 1.1795          | 0.815    |
| 0.1118        | 21.0  | 3150 | 1.1452          | 0.8117   |
| 0.2512        | 22.0  | 3300 | 1.1546          | 0.7983   |
| 0.1677        | 23.0  | 3450 | 1.0253          | 0.8183   |
| 0.0785        | 24.0  | 3600 | 1.0657          | 0.8267   |
| 0.0647        | 25.0  | 3750 | 1.2146          | 0.815    |
| 0.0165        | 26.0  | 3900 | 1.3062          | 0.8183   |
| 0.0259        | 27.0  | 4050 | 1.2518          | 0.81     |
| 0.1815        | 28.0  | 4200 | 1.1585          | 0.8033   |
| 0.1219        | 29.0  | 4350 | 1.0806          | 0.8133   |
| 0.0251        | 30.0  | 4500 | 1.4936          | 0.8033   |
| 0.039         | 31.0  | 4650 | 1.3547          | 0.8133   |
| 0.0615        | 32.0  | 4800 | 1.4443          | 0.7983   |
| 0.1655        | 33.0  | 4950 | 1.3331          | 0.8117   |
| 0.0194        | 34.0  | 5100 | 1.6769          | 0.795    |
| 0.0047        | 35.0  | 5250 | 1.5735          | 0.8083   |
| 0.0025        | 36.0  | 5400 | 1.4842          | 0.815    |
| 0.0043        | 37.0  | 5550 | 1.6737          | 0.8067   |
| 0.0066        | 38.0  | 5700 | 1.5953          | 0.81     |
| 0.0419        | 39.0  | 5850 | 1.4635          | 0.8033   |
| 0.0003        | 40.0  | 6000 | 1.5243          | 0.8083   |
| 0.0002        | 41.0  | 6150 | 1.6139          | 0.815    |
| 0.0184        | 42.0  | 6300 | 1.4432          | 0.8183   |
| 0.0108        | 43.0  | 6450 | 1.5909          | 0.8133   |
| 0.0152        | 44.0  | 6600 | 1.8318          | 0.8117   |
| 0.0333        | 45.0  | 6750 | 1.6573          | 0.8183   |
| 0.005         | 46.0  | 6900 | 1.7840          | 0.825    |
| 0.0002        | 47.0  | 7050 | 1.7494          | 0.8233   |
| 0.0           | 48.0  | 7200 | 1.7676          | 0.8267   |
| 0.047         | 49.0  | 7350 | 1.6725          | 0.825    |
| 0.0001        | 50.0  | 7500 | 1.6725          | 0.8233   |


### 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_lr0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8233333333333334, "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