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# SMIDS_1x_beit_large_SGD_lr0001_fold4

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: 0.5390
- Accuracy: 0.785

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4366        | 1.0   | 150  | 1.4760          | 0.295    |
| 1.3135        | 2.0   | 300  | 1.2744          | 0.3267   |
| 1.1192        | 3.0   | 450  | 1.1378          | 0.4083   |
| 1.0583        | 4.0   | 600  | 1.0489          | 0.4817   |
| 1.0113        | 5.0   | 750  | 0.9822          | 0.545    |
| 0.9561        | 6.0   | 900  | 0.9291          | 0.5833   |
| 0.9162        | 7.0   | 1050 | 0.8877          | 0.605    |
| 0.8723        | 8.0   | 1200 | 0.8549          | 0.615    |
| 0.8118        | 9.0   | 1350 | 0.8259          | 0.6283   |
| 0.7717        | 10.0  | 1500 | 0.8007          | 0.635    |
| 0.7883        | 11.0  | 1650 | 0.7785          | 0.645    |
| 0.7285        | 12.0  | 1800 | 0.7580          | 0.6633   |
| 0.7579        | 13.0  | 1950 | 0.7398          | 0.6733   |
| 0.7355        | 14.0  | 2100 | 0.7228          | 0.6883   |
| 0.7076        | 15.0  | 2250 | 0.7074          | 0.6967   |
| 0.7007        | 16.0  | 2400 | 0.6932          | 0.7083   |
| 0.7106        | 17.0  | 2550 | 0.6805          | 0.715    |
| 0.7252        | 18.0  | 2700 | 0.6688          | 0.7183   |
| 0.6932        | 19.0  | 2850 | 0.6578          | 0.725    |
| 0.7028        | 20.0  | 3000 | 0.6477          | 0.7283   |
| 0.6818        | 21.0  | 3150 | 0.6385          | 0.7317   |
| 0.6417        | 22.0  | 3300 | 0.6298          | 0.7383   |
| 0.6867        | 23.0  | 3450 | 0.6218          | 0.7433   |
| 0.6052        | 24.0  | 3600 | 0.6142          | 0.7467   |
| 0.5995        | 25.0  | 3750 | 0.6074          | 0.7533   |
| 0.6442        | 26.0  | 3900 | 0.6008          | 0.7567   |
| 0.6107        | 27.0  | 4050 | 0.5949          | 0.7633   |
| 0.6513        | 28.0  | 4200 | 0.5893          | 0.765    |
| 0.5873        | 29.0  | 4350 | 0.5841          | 0.7683   |
| 0.5848        | 30.0  | 4500 | 0.5792          | 0.77     |
| 0.6266        | 31.0  | 4650 | 0.5748          | 0.77     |
| 0.5541        | 32.0  | 4800 | 0.5708          | 0.7717   |
| 0.5323        | 33.0  | 4950 | 0.5669          | 0.7733   |
| 0.6182        | 34.0  | 5100 | 0.5634          | 0.775    |
| 0.6465        | 35.0  | 5250 | 0.5602          | 0.7767   |
| 0.5548        | 36.0  | 5400 | 0.5571          | 0.7783   |
| 0.6313        | 37.0  | 5550 | 0.5543          | 0.7783   |
| 0.5607        | 38.0  | 5700 | 0.5518          | 0.7817   |
| 0.5758        | 39.0  | 5850 | 0.5496          | 0.7817   |
| 0.5996        | 40.0  | 6000 | 0.5477          | 0.7817   |
| 0.516         | 41.0  | 6150 | 0.5459          | 0.7833   |
| 0.6072        | 42.0  | 6300 | 0.5444          | 0.785    |
| 0.5787        | 43.0  | 6450 | 0.5431          | 0.785    |
| 0.594         | 44.0  | 6600 | 0.5419          | 0.785    |
| 0.5458        | 45.0  | 6750 | 0.5409          | 0.785    |
| 0.5822        | 46.0  | 6900 | 0.5402          | 0.785    |
| 0.5368        | 47.0  | 7050 | 0.5396          | 0.785    |
| 0.5083        | 48.0  | 7200 | 0.5392          | 0.785    |
| 0.5733        | 49.0  | 7350 | 0.5390          | 0.785    |
| 0.5174        | 50.0  | 7500 | 0.5390          | 0.785    |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.785, "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