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# SMIDS_1x_beit_large_SGD_lr001_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: 0.2655
- Accuracy: 0.895

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8687        | 1.0   | 150  | 0.8183          | 0.635    |
| 0.7062        | 2.0   | 300  | 0.6176          | 0.7683   |
| 0.5065        | 3.0   | 450  | 0.5204          | 0.8033   |
| 0.4914        | 4.0   | 600  | 0.4635          | 0.825    |
| 0.4182        | 5.0   | 750  | 0.4220          | 0.8383   |
| 0.4335        | 6.0   | 900  | 0.3954          | 0.8417   |
| 0.4036        | 7.0   | 1050 | 0.3746          | 0.86     |
| 0.3782        | 8.0   | 1200 | 0.3573          | 0.8633   |
| 0.3437        | 9.0   | 1350 | 0.3443          | 0.8767   |
| 0.3429        | 10.0  | 1500 | 0.3316          | 0.8733   |
| 0.3838        | 11.0  | 1650 | 0.3224          | 0.875    |
| 0.3076        | 12.0  | 1800 | 0.3164          | 0.8817   |
| 0.2419        | 13.0  | 1950 | 0.3092          | 0.885    |
| 0.2608        | 14.0  | 2100 | 0.3041          | 0.8833   |
| 0.2093        | 15.0  | 2250 | 0.2992          | 0.885    |
| 0.2675        | 16.0  | 2400 | 0.2961          | 0.8867   |
| 0.2419        | 17.0  | 2550 | 0.2933          | 0.8867   |
| 0.2753        | 18.0  | 2700 | 0.2892          | 0.8883   |
| 0.2717        | 19.0  | 2850 | 0.2867          | 0.8883   |
| 0.2854        | 20.0  | 3000 | 0.2854          | 0.89     |
| 0.2351        | 21.0  | 3150 | 0.2829          | 0.8867   |
| 0.257         | 22.0  | 3300 | 0.2812          | 0.8867   |
| 0.2752        | 23.0  | 3450 | 0.2800          | 0.8867   |
| 0.2786        | 24.0  | 3600 | 0.2780          | 0.885    |
| 0.1823        | 25.0  | 3750 | 0.2754          | 0.8933   |
| 0.2794        | 26.0  | 3900 | 0.2752          | 0.8917   |
| 0.1762        | 27.0  | 4050 | 0.2735          | 0.89     |
| 0.3055        | 28.0  | 4200 | 0.2727          | 0.895    |
| 0.2896        | 29.0  | 4350 | 0.2713          | 0.89     |
| 0.2941        | 30.0  | 4500 | 0.2691          | 0.895    |
| 0.2451        | 31.0  | 4650 | 0.2699          | 0.8917   |
| 0.1554        | 32.0  | 4800 | 0.2693          | 0.8883   |
| 0.2043        | 33.0  | 4950 | 0.2681          | 0.8967   |
| 0.2029        | 34.0  | 5100 | 0.2683          | 0.8917   |
| 0.274         | 35.0  | 5250 | 0.2678          | 0.8983   |
| 0.1791        | 36.0  | 5400 | 0.2669          | 0.895    |
| 0.2104        | 37.0  | 5550 | 0.2674          | 0.8967   |
| 0.2032        | 38.0  | 5700 | 0.2666          | 0.8967   |
| 0.1496        | 39.0  | 5850 | 0.2660          | 0.8967   |
| 0.252         | 40.0  | 6000 | 0.2664          | 0.8933   |
| 0.1835        | 41.0  | 6150 | 0.2668          | 0.8983   |
| 0.2293        | 42.0  | 6300 | 0.2665          | 0.8983   |
| 0.183         | 43.0  | 6450 | 0.2662          | 0.8933   |
| 0.1769        | 44.0  | 6600 | 0.2654          | 0.8967   |
| 0.1669        | 45.0  | 6750 | 0.2657          | 0.895    |
| 0.1498        | 46.0  | 6900 | 0.2656          | 0.895    |
| 0.2371        | 47.0  | 7050 | 0.2657          | 0.895    |
| 0.1959        | 48.0  | 7200 | 0.2655          | 0.895    |
| 0.2551        | 49.0  | 7350 | 0.2654          | 0.895    |
| 0.1568        | 50.0  | 7500 | 0.2655          | 0.895    |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"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_SGD_lr001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.895, "name": "Accuracy"}]}]}]}
transformers safetensors 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