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# SMIDS_1x_beit_large_SGD_lr00001_fold5

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: 1.2148
- Accuracy: 0.37

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6389        | 1.0   | 150  | 1.6870          | 0.3017   |
| 1.6695        | 2.0   | 300  | 1.6604          | 0.3017   |
| 1.5177        | 3.0   | 450  | 1.6354          | 0.3017   |
| 1.627         | 4.0   | 600  | 1.6115          | 0.2967   |
| 1.5645        | 5.0   | 750  | 1.5885          | 0.2967   |
| 1.4875        | 6.0   | 900  | 1.5666          | 0.2967   |
| 1.4901        | 7.0   | 1050 | 1.5455          | 0.2933   |
| 1.5822        | 8.0   | 1200 | 1.5257          | 0.295    |
| 1.4781        | 9.0   | 1350 | 1.5066          | 0.295    |
| 1.4833        | 10.0  | 1500 | 1.4885          | 0.2967   |
| 1.5268        | 11.0  | 1650 | 1.4715          | 0.2917   |
| 1.4645        | 12.0  | 1800 | 1.4549          | 0.2883   |
| 1.4274        | 13.0  | 1950 | 1.4393          | 0.2933   |
| 1.4202        | 14.0  | 2100 | 1.4243          | 0.295    |
| 1.321         | 15.0  | 2250 | 1.4100          | 0.2933   |
| 1.3547        | 16.0  | 2400 | 1.3961          | 0.3017   |
| 1.442         | 17.0  | 2550 | 1.3831          | 0.305    |
| 1.3587        | 18.0  | 2700 | 1.3708          | 0.3083   |
| 1.2818        | 19.0  | 2850 | 1.3592          | 0.3067   |
| 1.2843        | 20.0  | 3000 | 1.3482          | 0.31     |
| 1.3882        | 21.0  | 3150 | 1.3376          | 0.3117   |
| 1.3927        | 22.0  | 3300 | 1.3277          | 0.3133   |
| 1.3031        | 23.0  | 3450 | 1.3185          | 0.3167   |
| 1.4001        | 24.0  | 3600 | 1.3097          | 0.3233   |
| 1.3375        | 25.0  | 3750 | 1.3014          | 0.3267   |
| 1.2957        | 26.0  | 3900 | 1.2935          | 0.3317   |
| 1.2962        | 27.0  | 4050 | 1.2863          | 0.34     |
| 1.2513        | 28.0  | 4200 | 1.2794          | 0.34     |
| 1.267         | 29.0  | 4350 | 1.2729          | 0.3483   |
| 1.3066        | 30.0  | 4500 | 1.2668          | 0.35     |
| 1.1674        | 31.0  | 4650 | 1.2611          | 0.3517   |
| 1.3019        | 32.0  | 4800 | 1.2558          | 0.355    |
| 1.2607        | 33.0  | 4950 | 1.2509          | 0.3583   |
| 1.225         | 34.0  | 5100 | 1.2463          | 0.3633   |
| 1.2524        | 35.0  | 5250 | 1.2421          | 0.365    |
| 1.2631        | 36.0  | 5400 | 1.2382          | 0.365    |
| 1.2017        | 37.0  | 5550 | 1.2347          | 0.3667   |
| 1.1837        | 38.0  | 5700 | 1.2315          | 0.3683   |
| 1.3006        | 39.0  | 5850 | 1.2287          | 0.3683   |
| 1.2384        | 40.0  | 6000 | 1.2261          | 0.3683   |
| 1.2721        | 41.0  | 6150 | 1.2237          | 0.3683   |
| 1.2122        | 42.0  | 6300 | 1.2217          | 0.3683   |
| 1.2978        | 43.0  | 6450 | 1.2200          | 0.3683   |
| 1.2871        | 44.0  | 6600 | 1.2185          | 0.37     |
| 1.3135        | 45.0  | 6750 | 1.2173          | 0.3717   |
| 1.2898        | 46.0  | 6900 | 1.2164          | 0.37     |
| 1.1655        | 47.0  | 7050 | 1.2157          | 0.37     |
| 1.2522        | 48.0  | 7200 | 1.2152          | 0.37     |
| 1.2377        | 49.0  | 7350 | 1.2149          | 0.37     |
| 1.242         | 50.0  | 7500 | 1.2148          | 0.37     |


### 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_SGD_lr00001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.37, "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