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# SMIDS_1x_beit_large_SGD_lr0001_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: 0.5540
- Accuracy: 0.7967

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4867        | 1.0   | 150  | 1.4625          | 0.2817   |
| 1.3964        | 2.0   | 300  | 1.2672          | 0.29     |
| 1.1244        | 3.0   | 450  | 1.1397          | 0.385    |
| 1.0361        | 4.0   | 600  | 1.0557          | 0.4617   |
| 0.9687        | 5.0   | 750  | 0.9932          | 0.52     |
| 0.9479        | 6.0   | 900  | 0.9456          | 0.545    |
| 0.8945        | 7.0   | 1050 | 0.9061          | 0.5767   |
| 0.8753        | 8.0   | 1200 | 0.8744          | 0.61     |
| 0.8296        | 9.0   | 1350 | 0.8462          | 0.62     |
| 0.8345        | 10.0  | 1500 | 0.8209          | 0.6433   |
| 0.8095        | 11.0  | 1650 | 0.7986          | 0.66     |
| 0.8481        | 12.0  | 1800 | 0.7783          | 0.67     |
| 0.7866        | 13.0  | 1950 | 0.7599          | 0.685    |
| 0.7571        | 14.0  | 2100 | 0.7427          | 0.6983   |
| 0.7184        | 15.0  | 2250 | 0.7276          | 0.7067   |
| 0.7124        | 16.0  | 2400 | 0.7134          | 0.7067   |
| 0.7174        | 17.0  | 2550 | 0.7000          | 0.7133   |
| 0.7066        | 18.0  | 2700 | 0.6881          | 0.7167   |
| 0.6918        | 19.0  | 2850 | 0.6770          | 0.7183   |
| 0.6813        | 20.0  | 3000 | 0.6666          | 0.7367   |
| 0.6668        | 21.0  | 3150 | 0.6568          | 0.7417   |
| 0.6396        | 22.0  | 3300 | 0.6477          | 0.7483   |
| 0.6862        | 23.0  | 3450 | 0.6395          | 0.7567   |
| 0.6706        | 24.0  | 3600 | 0.6316          | 0.765    |
| 0.5976        | 25.0  | 3750 | 0.6244          | 0.7633   |
| 0.6713        | 26.0  | 3900 | 0.6177          | 0.7633   |
| 0.5642        | 27.0  | 4050 | 0.6116          | 0.7667   |
| 0.5986        | 28.0  | 4200 | 0.6059          | 0.77     |
| 0.6228        | 29.0  | 4350 | 0.6004          | 0.775    |
| 0.6562        | 30.0  | 4500 | 0.5954          | 0.78     |
| 0.6314        | 31.0  | 4650 | 0.5908          | 0.78     |
| 0.562         | 32.0  | 4800 | 0.5866          | 0.78     |
| 0.5892        | 33.0  | 4950 | 0.5828          | 0.7833   |
| 0.5506        | 34.0  | 5100 | 0.5792          | 0.7867   |
| 0.6391        | 35.0  | 5250 | 0.5758          | 0.7883   |
| 0.5824        | 36.0  | 5400 | 0.5725          | 0.7883   |
| 0.5968        | 37.0  | 5550 | 0.5697          | 0.7883   |
| 0.6168        | 38.0  | 5700 | 0.5671          | 0.79     |
| 0.5736        | 39.0  | 5850 | 0.5649          | 0.7883   |
| 0.5435        | 40.0  | 6000 | 0.5628          | 0.7867   |
| 0.636         | 41.0  | 6150 | 0.5610          | 0.7917   |
| 0.5897        | 42.0  | 6300 | 0.5594          | 0.7917   |
| 0.5639        | 43.0  | 6450 | 0.5581          | 0.7933   |
| 0.5393        | 44.0  | 6600 | 0.5569          | 0.7933   |
| 0.549         | 45.0  | 6750 | 0.5560          | 0.795    |
| 0.5296        | 46.0  | 6900 | 0.5552          | 0.795    |
| 0.5463        | 47.0  | 7050 | 0.5546          | 0.795    |
| 0.5393        | 48.0  | 7200 | 0.5542          | 0.795    |
| 0.6667        | 49.0  | 7350 | 0.5540          | 0.7967   |
| 0.5424        | 50.0  | 7500 | 0.5540          | 0.7967   |


### 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_lr0001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7966666666666666, "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