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# SMIDS_1x_beit_large_RMSProp_lr00001_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: 1.1341
- Accuracy: 0.8902

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2859        | 1.0   | 150  | 0.3014          | 0.8785   |
| 0.1993        | 2.0   | 300  | 0.2794          | 0.8819   |
| 0.0666        | 3.0   | 450  | 0.4895          | 0.8918   |
| 0.0887        | 4.0   | 600  | 0.5141          | 0.8819   |
| 0.1184        | 5.0   | 750  | 0.4988          | 0.8935   |
| 0.0371        | 6.0   | 900  | 0.6458          | 0.8968   |
| 0.0224        | 7.0   | 1050 | 0.5957          | 0.9018   |
| 0.1056        | 8.0   | 1200 | 0.6872          | 0.9018   |
| 0.0001        | 9.0   | 1350 | 0.7184          | 0.9018   |
| 0.0413        | 10.0  | 1500 | 0.8802          | 0.8885   |
| 0.0011        | 11.0  | 1650 | 0.8377          | 0.9035   |
| 0.0725        | 12.0  | 1800 | 0.8651          | 0.9018   |
| 0.0048        | 13.0  | 1950 | 0.8577          | 0.8985   |
| 0.0147        | 14.0  | 2100 | 0.7885          | 0.9002   |
| 0.0258        | 15.0  | 2250 | 0.8956          | 0.9085   |
| 0.0016        | 16.0  | 2400 | 0.9094          | 0.9002   |
| 0.0002        | 17.0  | 2550 | 0.8443          | 0.9035   |
| 0.0           | 18.0  | 2700 | 0.8496          | 0.9052   |
| 0.0209        | 19.0  | 2850 | 0.9123          | 0.9002   |
| 0.033         | 20.0  | 3000 | 0.9276          | 0.8985   |
| 0.0           | 21.0  | 3150 | 0.9402          | 0.9085   |
| 0.0048        | 22.0  | 3300 | 0.9848          | 0.8985   |
| 0.0001        | 23.0  | 3450 | 0.9787          | 0.9002   |
| 0.0566        | 24.0  | 3600 | 0.8818          | 0.9052   |
| 0.0176        | 25.0  | 3750 | 0.9386          | 0.9101   |
| 0.0065        | 26.0  | 3900 | 0.9541          | 0.9052   |
| 0.0           | 27.0  | 4050 | 1.0433          | 0.8985   |
| 0.0185        | 28.0  | 4200 | 1.0054          | 0.9035   |
| 0.0           | 29.0  | 4350 | 1.0675          | 0.8935   |
| 0.0           | 30.0  | 4500 | 1.1325          | 0.8869   |
| 0.0           | 31.0  | 4650 | 1.0249          | 0.9068   |
| 0.0           | 32.0  | 4800 | 1.0505          | 0.9002   |
| 0.0           | 33.0  | 4950 | 1.0925          | 0.8968   |
| 0.0           | 34.0  | 5100 | 1.0973          | 0.8968   |
| 0.0           | 35.0  | 5250 | 1.0443          | 0.8952   |
| 0.0           | 36.0  | 5400 | 1.1234          | 0.8918   |
| 0.0           | 37.0  | 5550 | 1.0997          | 0.8918   |
| 0.0           | 38.0  | 5700 | 1.2085          | 0.8918   |
| 0.0           | 39.0  | 5850 | 1.1773          | 0.8885   |
| 0.0           | 40.0  | 6000 | 1.1092          | 0.8968   |
| 0.0           | 41.0  | 6150 | 1.1503          | 0.8869   |
| 0.0057        | 42.0  | 6300 | 1.1551          | 0.8869   |
| 0.0           | 43.0  | 6450 | 1.1499          | 0.8885   |
| 0.0           | 44.0  | 6600 | 1.1482          | 0.8902   |
| 0.0           | 45.0  | 6750 | 1.1492          | 0.8885   |
| 0.0           | 46.0  | 6900 | 1.1494          | 0.8869   |
| 0.0           | 47.0  | 7050 | 1.1416          | 0.8885   |
| 0.0           | 48.0  | 7200 | 1.1345          | 0.8869   |
| 0.0           | 49.0  | 7350 | 1.1354          | 0.8885   |
| 0.0           | 50.0  | 7500 | 1.1341          | 0.8902   |


### 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_RMSProp_lr00001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8901830282861897, "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