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# SMIDS_1x_beit_large_Adamax_lr0001_fold3

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: 0.8823
- Accuracy: 0.9167

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3336        | 1.0   | 150  | 0.2867          | 0.8917   |
| 0.43          | 2.0   | 300  | 0.3557          | 0.8717   |
| 0.0828        | 3.0   | 450  | 0.4549          | 0.8867   |
| 0.087         | 4.0   | 600  | 0.4448          | 0.91     |
| 0.0569        | 5.0   | 750  | 0.4224          | 0.9183   |
| 0.0312        | 6.0   | 900  | 0.5662          | 0.91     |
| 0.0725        | 7.0   | 1050 | 0.7421          | 0.895    |
| 0.0003        | 8.0   | 1200 | 0.5652          | 0.9217   |
| 0.0421        | 9.0   | 1350 | 0.7408          | 0.9      |
| 0.0014        | 10.0  | 1500 | 0.6240          | 0.91     |
| 0.0           | 11.0  | 1650 | 0.6933          | 0.9167   |
| 0.0001        | 12.0  | 1800 | 0.6759          | 0.915    |
| 0.0436        | 13.0  | 1950 | 0.5776          | 0.9117   |
| 0.0001        | 14.0  | 2100 | 0.6369          | 0.9067   |
| 0.0           | 15.0  | 2250 | 0.6545          | 0.925    |
| 0.0           | 16.0  | 2400 | 0.6392          | 0.9233   |
| 0.0           | 17.0  | 2550 | 0.7112          | 0.9133   |
| 0.021         | 18.0  | 2700 | 0.7031          | 0.92     |
| 0.0           | 19.0  | 2850 | 0.7309          | 0.9033   |
| 0.0506        | 20.0  | 3000 | 0.7566          | 0.9117   |
| 0.0           | 21.0  | 3150 | 0.8407          | 0.905    |
| 0.0001        | 22.0  | 3300 | 0.8215          | 0.9083   |
| 0.0           | 23.0  | 3450 | 0.8294          | 0.905    |
| 0.0           | 24.0  | 3600 | 0.7680          | 0.91     |
| 0.0           | 25.0  | 3750 | 0.8414          | 0.9117   |
| 0.0           | 26.0  | 3900 | 0.8087          | 0.9017   |
| 0.0074        | 27.0  | 4050 | 0.7837          | 0.9117   |
| 0.0           | 28.0  | 4200 | 0.7877          | 0.915    |
| 0.0           | 29.0  | 4350 | 0.7862          | 0.92     |
| 0.0           | 30.0  | 4500 | 0.8077          | 0.9167   |
| 0.0           | 31.0  | 4650 | 0.8122          | 0.9167   |
| 0.0           | 32.0  | 4800 | 0.8183          | 0.915    |
| 0.0096        | 33.0  | 4950 | 0.8311          | 0.9133   |
| 0.0           | 34.0  | 5100 | 0.8366          | 0.9183   |
| 0.0           | 35.0  | 5250 | 0.8688          | 0.9117   |
| 0.0096        | 36.0  | 5400 | 0.8673          | 0.9083   |
| 0.0           | 37.0  | 5550 | 0.8841          | 0.9083   |
| 0.0           | 38.0  | 5700 | 0.8799          | 0.9133   |
| 0.0           | 39.0  | 5850 | 0.8836          | 0.9167   |
| 0.0           | 40.0  | 6000 | 0.8797          | 0.91     |
| 0.0           | 41.0  | 6150 | 0.8668          | 0.9167   |
| 0.0           | 42.0  | 6300 | 0.8726          | 0.92     |
| 0.0062        | 43.0  | 6450 | 0.8776          | 0.9167   |
| 0.0           | 44.0  | 6600 | 0.8787          | 0.9183   |
| 0.0087        | 45.0  | 6750 | 0.8835          | 0.9183   |
| 0.0           | 46.0  | 6900 | 0.8788          | 0.9167   |
| 0.0038        | 47.0  | 7050 | 0.8773          | 0.9167   |
| 0.0           | 48.0  | 7200 | 0.8817          | 0.9167   |
| 0.0           | 49.0  | 7350 | 0.8819          | 0.9167   |
| 0.0           | 50.0  | 7500 | 0.8823          | 0.9167   |


### 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_Adamax_lr0001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9166666666666666, "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