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# SMIDS_1x_beit_large_SGD_lr001_fold2

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: 0.2671
- Accuracy: 0.9052

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8448        | 1.0   | 150  | 0.7786          | 0.6822   |
| 0.5919        | 2.0   | 300  | 0.5894          | 0.7720   |
| 0.5201        | 3.0   | 450  | 0.4896          | 0.8103   |
| 0.4726        | 4.0   | 600  | 0.4316          | 0.8369   |
| 0.4395        | 5.0   | 750  | 0.3932          | 0.8486   |
| 0.3822        | 6.0   | 900  | 0.3637          | 0.8619   |
| 0.3938        | 7.0   | 1050 | 0.3468          | 0.8669   |
| 0.3759        | 8.0   | 1200 | 0.3315          | 0.8735   |
| 0.3107        | 9.0   | 1350 | 0.3182          | 0.8802   |
| 0.3377        | 10.0  | 1500 | 0.3121          | 0.8802   |
| 0.3018        | 11.0  | 1650 | 0.3033          | 0.8918   |
| 0.3236        | 12.0  | 1800 | 0.2967          | 0.8952   |
| 0.3126        | 13.0  | 1950 | 0.2923          | 0.8968   |
| 0.3692        | 14.0  | 2100 | 0.2917          | 0.8869   |
| 0.3005        | 15.0  | 2250 | 0.2863          | 0.8902   |
| 0.3076        | 16.0  | 2400 | 0.2835          | 0.8902   |
| 0.3141        | 17.0  | 2550 | 0.2803          | 0.8935   |
| 0.2324        | 18.0  | 2700 | 0.2776          | 0.8952   |
| 0.2244        | 19.0  | 2850 | 0.2769          | 0.8935   |
| 0.2389        | 20.0  | 3000 | 0.2770          | 0.8968   |
| 0.2315        | 21.0  | 3150 | 0.2755          | 0.8985   |
| 0.2776        | 22.0  | 3300 | 0.2743          | 0.8985   |
| 0.2209        | 23.0  | 3450 | 0.2766          | 0.8968   |
| 0.2374        | 24.0  | 3600 | 0.2712          | 0.9035   |
| 0.1894        | 25.0  | 3750 | 0.2687          | 0.9068   |
| 0.1669        | 26.0  | 3900 | 0.2700          | 0.9035   |
| 0.2198        | 27.0  | 4050 | 0.2706          | 0.9035   |
| 0.2092        | 28.0  | 4200 | 0.2730          | 0.8985   |
| 0.1753        | 29.0  | 4350 | 0.2700          | 0.9052   |
| 0.2229        | 30.0  | 4500 | 0.2689          | 0.9068   |
| 0.2544        | 31.0  | 4650 | 0.2696          | 0.9018   |
| 0.1915        | 32.0  | 4800 | 0.2666          | 0.9085   |
| 0.1644        | 33.0  | 4950 | 0.2671          | 0.9052   |
| 0.2329        | 34.0  | 5100 | 0.2677          | 0.9085   |
| 0.1884        | 35.0  | 5250 | 0.2691          | 0.9002   |
| 0.2339        | 36.0  | 5400 | 0.2688          | 0.9052   |
| 0.2163        | 37.0  | 5550 | 0.2684          | 0.9035   |
| 0.1424        | 38.0  | 5700 | 0.2693          | 0.9035   |
| 0.2292        | 39.0  | 5850 | 0.2675          | 0.9035   |
| 0.1541        | 40.0  | 6000 | 0.2675          | 0.9035   |
| 0.1794        | 41.0  | 6150 | 0.2672          | 0.9052   |
| 0.1686        | 42.0  | 6300 | 0.2678          | 0.9018   |
| 0.2872        | 43.0  | 6450 | 0.2681          | 0.9018   |
| 0.2264        | 44.0  | 6600 | 0.2679          | 0.9018   |
| 0.1729        | 45.0  | 6750 | 0.2671          | 0.9052   |
| 0.2083        | 46.0  | 6900 | 0.2671          | 0.9035   |
| 0.2063        | 47.0  | 7050 | 0.2671          | 0.9052   |
| 0.185         | 48.0  | 7200 | 0.2670          | 0.9052   |
| 0.1787        | 49.0  | 7350 | 0.2671          | 0.9052   |
| 0.2077        | 50.0  | 7500 | 0.2671          | 0.9052   |


### 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_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9051580698835274, "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