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# SMIDS_1x_beit_large_SGD_lr00001_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: 1.2222
- Accuracy: 0.3233

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.683         | 1.0   | 150  | 1.6853          | 0.2933   |
| 1.7535        | 2.0   | 300  | 1.6591          | 0.29     |
| 1.5972        | 3.0   | 450  | 1.6342          | 0.2883   |
| 1.5424        | 4.0   | 600  | 1.6105          | 0.2883   |
| 1.4999        | 5.0   | 750  | 1.5877          | 0.2883   |
| 1.4779        | 6.0   | 900  | 1.5661          | 0.29     |
| 1.428         | 7.0   | 1050 | 1.5452          | 0.2883   |
| 1.5724        | 8.0   | 1200 | 1.5257          | 0.285    |
| 1.4081        | 9.0   | 1350 | 1.5067          | 0.2867   |
| 1.4484        | 10.0  | 1500 | 1.4888          | 0.285    |
| 1.5053        | 11.0  | 1650 | 1.4718          | 0.2817   |
| 1.5245        | 12.0  | 1800 | 1.4555          | 0.28     |
| 1.4851        | 13.0  | 1950 | 1.4401          | 0.2733   |
| 1.4338        | 14.0  | 2100 | 1.4254          | 0.2733   |
| 1.3314        | 15.0  | 2250 | 1.4114          | 0.2733   |
| 1.4525        | 16.0  | 2400 | 1.3979          | 0.275    |
| 1.4438        | 17.0  | 2550 | 1.3852          | 0.28     |
| 1.376         | 18.0  | 2700 | 1.3733          | 0.2783   |
| 1.3912        | 19.0  | 2850 | 1.3620          | 0.2783   |
| 1.3095        | 20.0  | 3000 | 1.3514          | 0.2767   |
| 1.3547        | 21.0  | 3150 | 1.3411          | 0.275    |
| 1.3592        | 22.0  | 3300 | 1.3315          | 0.2783   |
| 1.3531        | 23.0  | 3450 | 1.3225          | 0.2833   |
| 1.3511        | 24.0  | 3600 | 1.3139          | 0.2817   |
| 1.2946        | 25.0  | 3750 | 1.3059          | 0.2833   |
| 1.3239        | 26.0  | 3900 | 1.2984          | 0.2883   |
| 1.2264        | 27.0  | 4050 | 1.2912          | 0.2867   |
| 1.2629        | 28.0  | 4200 | 1.2844          | 0.2833   |
| 1.2471        | 29.0  | 4350 | 1.2782          | 0.2867   |
| 1.3227        | 30.0  | 4500 | 1.2723          | 0.29     |
| 1.2498        | 31.0  | 4650 | 1.2668          | 0.29     |
| 1.3238        | 32.0  | 4800 | 1.2617          | 0.2917   |
| 1.2473        | 33.0  | 4950 | 1.2570          | 0.2967   |
| 1.2174        | 34.0  | 5100 | 1.2526          | 0.3033   |
| 1.2359        | 35.0  | 5250 | 1.2485          | 0.305    |
| 1.2175        | 36.0  | 5400 | 1.2447          | 0.3083   |
| 1.2527        | 37.0  | 5550 | 1.2413          | 0.31     |
| 1.3105        | 38.0  | 5700 | 1.2382          | 0.3117   |
| 1.2578        | 39.0  | 5850 | 1.2355          | 0.3133   |
| 1.2096        | 40.0  | 6000 | 1.2330          | 0.3167   |
| 1.3711        | 41.0  | 6150 | 1.2308          | 0.315    |
| 1.1858        | 42.0  | 6300 | 1.2289          | 0.3167   |
| 1.2631        | 43.0  | 6450 | 1.2272          | 0.3167   |
| 1.2044        | 44.0  | 6600 | 1.2258          | 0.3183   |
| 1.2219        | 45.0  | 6750 | 1.2246          | 0.32     |
| 1.2411        | 46.0  | 6900 | 1.2237          | 0.3217   |
| 1.164         | 47.0  | 7050 | 1.2230          | 0.3217   |
| 1.2162        | 48.0  | 7200 | 1.2225          | 0.3217   |
| 1.3094        | 49.0  | 7350 | 1.2222          | 0.3233   |
| 1.1791        | 50.0  | 7500 | 1.2222          | 0.3233   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.3233333333333333, "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