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# SMIDS_1x_beit_large_RMSProp_lr0001_fold1

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: 1.7877
- Accuracy: 0.7997

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8302        | 1.0   | 151  | 0.8344          | 0.5609   |
| 0.7715        | 2.0   | 302  | 0.8057          | 0.5643   |
| 0.7737        | 3.0   | 453  | 0.7728          | 0.5810   |
| 0.6718        | 4.0   | 604  | 1.8574          | 0.5910   |
| 0.6918        | 5.0   | 755  | 0.8493          | 0.6461   |
| 0.6362        | 6.0   | 906  | 0.6865          | 0.6912   |
| 0.5577        | 7.0   | 1057 | 0.8540          | 0.6895   |
| 0.5066        | 8.0   | 1208 | 0.6058          | 0.7279   |
| 0.5441        | 9.0   | 1359 | 0.8240          | 0.7028   |
| 0.4804        | 10.0  | 1510 | 0.7419          | 0.7279   |
| 0.3671        | 11.0  | 1661 | 0.6805          | 0.7579   |
| 0.4347        | 12.0  | 1812 | 0.6727          | 0.7629   |
| 0.3855        | 13.0  | 1963 | 0.6134          | 0.7613   |
| 0.3813        | 14.0  | 2114 | 0.7491          | 0.7596   |
| 0.2018        | 15.0  | 2265 | 0.9024          | 0.7446   |
| 0.2039        | 16.0  | 2416 | 0.8463          | 0.7462   |
| 0.2623        | 17.0  | 2567 | 0.7505          | 0.7713   |
| 0.145         | 18.0  | 2718 | 0.8386          | 0.7596   |
| 0.2105        | 19.0  | 2869 | 0.8808          | 0.7679   |
| 0.078         | 20.0  | 3020 | 0.9712          | 0.7746   |
| 0.2757        | 21.0  | 3171 | 1.3825          | 0.7596   |
| 0.1553        | 22.0  | 3322 | 1.0660          | 0.7730   |
| 0.1299        | 23.0  | 3473 | 1.2242          | 0.7813   |
| 0.1775        | 24.0  | 3624 | 1.2795          | 0.7713   |
| 0.0986        | 25.0  | 3775 | 1.0377          | 0.7830   |
| 0.0732        | 26.0  | 3926 | 1.4568          | 0.7880   |
| 0.0535        | 27.0  | 4077 | 1.4001          | 0.7730   |
| 0.1205        | 28.0  | 4228 | 1.2895          | 0.7913   |
| 0.0046        | 29.0  | 4379 | 1.5678          | 0.7796   |
| 0.0037        | 30.0  | 4530 | 1.5094          | 0.7863   |
| 0.0878        | 31.0  | 4681 | 1.4944          | 0.7596   |
| 0.0878        | 32.0  | 4832 | 1.5249          | 0.7997   |
| 0.0288        | 33.0  | 4983 | 1.4887          | 0.7846   |
| 0.0377        | 34.0  | 5134 | 1.4602          | 0.7846   |
| 0.0466        | 35.0  | 5285 | 1.6048          | 0.7730   |
| 0.0118        | 36.0  | 5436 | 1.5238          | 0.7930   |
| 0.0671        | 37.0  | 5587 | 1.5811          | 0.7880   |
| 0.0354        | 38.0  | 5738 | 1.5909          | 0.7830   |
| 0.0786        | 39.0  | 5889 | 1.4869          | 0.7930   |
| 0.093         | 40.0  | 6040 | 1.5572          | 0.7896   |
| 0.0002        | 41.0  | 6191 | 1.8399          | 0.7830   |
| 0.0031        | 42.0  | 6342 | 1.7427          | 0.7780   |
| 0.0542        | 43.0  | 6493 | 1.9256          | 0.7880   |
| 0.0007        | 44.0  | 6644 | 1.9462          | 0.7930   |
| 0.0079        | 45.0  | 6795 | 2.0379          | 0.7930   |
| 0.0           | 46.0  | 6946 | 1.9880          | 0.8030   |
| 0.0196        | 47.0  | 7097 | 1.7536          | 0.8013   |
| 0.006         | 48.0  | 7248 | 1.8419          | 0.7963   |
| 0.0289        | 49.0  | 7399 | 1.7771          | 0.7980   |
| 0.0           | 50.0  | 7550 | 1.7877          | 0.7997   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7996661101836394, "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