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# SMIDS_1x_beit_large_RMSProp_lr00001_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: 0.9663
- Accuracy: 0.9115

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3301        | 1.0   | 151  | 0.2821          | 0.9032   |
| 0.1587        | 2.0   | 302  | 0.4948          | 0.8347   |
| 0.1718        | 3.0   | 453  | 0.4205          | 0.8948   |
| 0.0066        | 4.0   | 604  | 0.5707          | 0.8915   |
| 0.0469        | 5.0   | 755  | 0.6116          | 0.8998   |
| 0.0627        | 6.0   | 906  | 0.6124          | 0.9015   |
| 0.0172        | 7.0   | 1057 | 0.7242          | 0.8848   |
| 0.002         | 8.0   | 1208 | 0.5765          | 0.9065   |
| 0.0331        | 9.0   | 1359 | 0.5639          | 0.9065   |
| 0.0548        | 10.0  | 1510 | 0.7553          | 0.8932   |
| 0.1067        | 11.0  | 1661 | 0.7210          | 0.8982   |
| 0.0481        | 12.0  | 1812 | 0.6793          | 0.8965   |
| 0.0038        | 13.0  | 1963 | 0.9371          | 0.8781   |
| 0.0112        | 14.0  | 2114 | 0.8408          | 0.8965   |
| 0.0005        | 15.0  | 2265 | 0.8828          | 0.8932   |
| 0.0003        | 16.0  | 2416 | 0.7751          | 0.9082   |
| 0.0131        | 17.0  | 2567 | 0.9739          | 0.8932   |
| 0.0           | 18.0  | 2718 | 0.9107          | 0.8998   |
| 0.0           | 19.0  | 2869 | 0.7727          | 0.9115   |
| 0.0396        | 20.0  | 3020 | 0.8297          | 0.9098   |
| 0.0167        | 21.0  | 3171 | 0.9247          | 0.9015   |
| 0.013         | 22.0  | 3322 | 1.1123          | 0.8815   |
| 0.0           | 23.0  | 3473 | 0.8463          | 0.9048   |
| 0.017         | 24.0  | 3624 | 1.0171          | 0.8965   |
| 0.0048        | 25.0  | 3775 | 0.8518          | 0.9098   |
| 0.0           | 26.0  | 3926 | 0.8383          | 0.9115   |
| 0.0           | 27.0  | 4077 | 0.9813          | 0.9032   |
| 0.0           | 28.0  | 4228 | 0.9050          | 0.8998   |
| 0.0           | 29.0  | 4379 | 0.9000          | 0.9048   |
| 0.0           | 30.0  | 4530 | 0.8872          | 0.9082   |
| 0.006         | 31.0  | 4681 | 0.9047          | 0.9048   |
| 0.0133        | 32.0  | 4832 | 0.8691          | 0.9115   |
| 0.0           | 33.0  | 4983 | 0.9895          | 0.8998   |
| 0.0           | 34.0  | 5134 | 0.9681          | 0.9048   |
| 0.0047        | 35.0  | 5285 | 0.8855          | 0.9048   |
| 0.0           | 36.0  | 5436 | 0.9879          | 0.8965   |
| 0.0131        | 37.0  | 5587 | 0.9825          | 0.8998   |
| 0.0           | 38.0  | 5738 | 0.9641          | 0.8982   |
| 0.0045        | 39.0  | 5889 | 0.9681          | 0.9048   |
| 0.0           | 40.0  | 6040 | 1.1064          | 0.9032   |
| 0.0           | 41.0  | 6191 | 0.9908          | 0.9098   |
| 0.0           | 42.0  | 6342 | 0.9736          | 0.9082   |
| 0.007         | 43.0  | 6493 | 1.0120          | 0.9098   |
| 0.0           | 44.0  | 6644 | 0.9964          | 0.9098   |
| 0.0           | 45.0  | 6795 | 0.9972          | 0.9082   |
| 0.0           | 46.0  | 6946 | 0.9332          | 0.9132   |
| 0.0           | 47.0  | 7097 | 0.9483          | 0.9082   |
| 0.0053        | 48.0  | 7248 | 0.9532          | 0.9098   |
| 0.0037        | 49.0  | 7399 | 0.9671          | 0.9132   |
| 0.0           | 50.0  | 7550 | 0.9663          | 0.9115   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9115191986644408, "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