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# SMIDS_1x_beit_large_Adamax_lr0001_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: 1.3342
- Accuracy: 0.88

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3818        | 1.0   | 150  | 0.3825          | 0.8483   |
| 0.2269        | 2.0   | 300  | 0.4138          | 0.87     |
| 0.0994        | 3.0   | 450  | 0.5782          | 0.865    |
| 0.1176        | 4.0   | 600  | 0.5919          | 0.865    |
| 0.0221        | 5.0   | 750  | 0.8233          | 0.8883   |
| 0.0257        | 6.0   | 900  | 0.9030          | 0.8733   |
| 0.001         | 7.0   | 1050 | 0.9758          | 0.8683   |
| 0.0349        | 8.0   | 1200 | 0.9331          | 0.88     |
| 0.0005        | 9.0   | 1350 | 0.9911          | 0.865    |
| 0.0075        | 10.0  | 1500 | 1.0490          | 0.87     |
| 0.0033        | 11.0  | 1650 | 0.9742          | 0.88     |
| 0.0           | 12.0  | 1800 | 1.0638          | 0.8717   |
| 0.0312        | 13.0  | 1950 | 1.0272          | 0.8817   |
| 0.0           | 14.0  | 2100 | 1.0299          | 0.8817   |
| 0.0           | 15.0  | 2250 | 1.0297          | 0.885    |
| 0.0           | 16.0  | 2400 | 1.0473          | 0.8867   |
| 0.0           | 17.0  | 2550 | 1.0713          | 0.8833   |
| 0.0086        | 18.0  | 2700 | 1.1112          | 0.88     |
| 0.0           | 19.0  | 2850 | 1.1002          | 0.8817   |
| 0.0135        | 20.0  | 3000 | 1.0746          | 0.8817   |
| 0.0           | 21.0  | 3150 | 1.2154          | 0.89     |
| 0.0           | 22.0  | 3300 | 1.2374          | 0.8733   |
| 0.0003        | 23.0  | 3450 | 1.2089          | 0.885    |
| 0.0           | 24.0  | 3600 | 1.2022          | 0.8783   |
| 0.0001        | 25.0  | 3750 | 1.2100          | 0.8817   |
| 0.0           | 26.0  | 3900 | 1.2077          | 0.875    |
| 0.0           | 27.0  | 4050 | 1.2711          | 0.885    |
| 0.0           | 28.0  | 4200 | 1.2384          | 0.875    |
| 0.0001        | 29.0  | 4350 | 1.2603          | 0.875    |
| 0.0           | 30.0  | 4500 | 1.2492          | 0.88     |
| 0.0           | 31.0  | 4650 | 1.2820          | 0.8783   |
| 0.0           | 32.0  | 4800 | 1.2664          | 0.88     |
| 0.0           | 33.0  | 4950 | 1.3025          | 0.88     |
| 0.0           | 34.0  | 5100 | 1.3025          | 0.8817   |
| 0.0           | 35.0  | 5250 | 1.3063          | 0.8817   |
| 0.0           | 36.0  | 5400 | 1.3072          | 0.885    |
| 0.0112        | 37.0  | 5550 | 1.3004          | 0.8833   |
| 0.0           | 38.0  | 5700 | 1.3132          | 0.8767   |
| 0.0058        | 39.0  | 5850 | 1.3322          | 0.875    |
| 0.0           | 40.0  | 6000 | 1.3249          | 0.8767   |
| 0.0           | 41.0  | 6150 | 1.3239          | 0.8783   |
| 0.0061        | 42.0  | 6300 | 1.3295          | 0.875    |
| 0.0           | 43.0  | 6450 | 1.3204          | 0.8783   |
| 0.0           | 44.0  | 6600 | 1.3178          | 0.8767   |
| 0.0           | 45.0  | 6750 | 1.3305          | 0.8783   |
| 0.0           | 46.0  | 6900 | 1.3298          | 0.8767   |
| 0.0           | 47.0  | 7050 | 1.3290          | 0.8783   |
| 0.0           | 48.0  | 7200 | 1.3361          | 0.8767   |
| 0.0           | 49.0  | 7350 | 1.3342          | 0.8817   |
| 0.0           | 50.0  | 7500 | 1.3342          | 0.88     |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.88, "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