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# SMIDS_1x_beit_large_Adamax_lr001_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: 1.5974
- Accuracy: 0.7970

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9629        | 1.0   | 150  | 0.8526          | 0.5308   |
| 0.8561        | 2.0   | 300  | 0.8135          | 0.5641   |
| 0.7482        | 3.0   | 450  | 0.7746          | 0.6023   |
| 0.7828        | 4.0   | 600  | 0.7357          | 0.6339   |
| 0.702         | 5.0   | 750  | 0.8736          | 0.6090   |
| 0.6968        | 6.0   | 900  | 0.6888          | 0.6789   |
| 0.7399        | 7.0   | 1050 | 0.6914          | 0.6639   |
| 0.5673        | 8.0   | 1200 | 0.5951          | 0.7654   |
| 0.4816        | 9.0   | 1350 | 0.5935          | 0.7654   |
| 0.6033        | 10.0  | 1500 | 0.6798          | 0.7105   |
| 0.541         | 11.0  | 1650 | 0.5320          | 0.7754   |
| 0.5436        | 12.0  | 1800 | 0.5281          | 0.7903   |
| 0.4696        | 13.0  | 1950 | 0.6121          | 0.7820   |
| 0.5274        | 14.0  | 2100 | 0.5275          | 0.7903   |
| 0.3349        | 15.0  | 2250 | 0.5852          | 0.7887   |
| 0.4894        | 16.0  | 2400 | 0.5107          | 0.7937   |
| 0.4202        | 17.0  | 2550 | 0.5575          | 0.7887   |
| 0.3089        | 18.0  | 2700 | 0.5163          | 0.8120   |
| 0.3785        | 19.0  | 2850 | 0.5485          | 0.7804   |
| 0.254         | 20.0  | 3000 | 0.5674          | 0.8136   |
| 0.3016        | 21.0  | 3150 | 0.7020          | 0.8020   |
| 0.263         | 22.0  | 3300 | 0.6876          | 0.7987   |
| 0.4071        | 23.0  | 3450 | 0.6714          | 0.8103   |
| 0.2983        | 24.0  | 3600 | 0.7244          | 0.7937   |
| 0.2094        | 25.0  | 3750 | 0.6489          | 0.7920   |
| 0.3941        | 26.0  | 3900 | 0.8690          | 0.7970   |
| 0.185         | 27.0  | 4050 | 1.1823          | 0.7953   |
| 0.1201        | 28.0  | 4200 | 0.8215          | 0.7920   |
| 0.2181        | 29.0  | 4350 | 1.0806          | 0.7987   |
| 0.1424        | 30.0  | 4500 | 1.1564          | 0.8136   |
| 0.1433        | 31.0  | 4650 | 1.2783          | 0.7887   |
| 0.0212        | 32.0  | 4800 | 1.4782          | 0.7920   |
| 0.075         | 33.0  | 4950 | 1.4769          | 0.7920   |
| 0.0734        | 34.0  | 5100 | 1.4691          | 0.8020   |
| 0.1033        | 35.0  | 5250 | 1.3308          | 0.8037   |
| 0.0491        | 36.0  | 5400 | 1.5122          | 0.7970   |
| 0.0008        | 37.0  | 5550 | 1.4694          | 0.8053   |
| 0.0017        | 38.0  | 5700 | 1.4299          | 0.7970   |
| 0.025         | 39.0  | 5850 | 1.4418          | 0.7887   |
| 0.0304        | 40.0  | 6000 | 1.4959          | 0.7937   |
| 0.0067        | 41.0  | 6150 | 1.4036          | 0.8053   |
| 0.012         | 42.0  | 6300 | 1.5265          | 0.8020   |
| 0.0219        | 43.0  | 6450 | 1.4700          | 0.7887   |
| 0.0003        | 44.0  | 6600 | 1.6579          | 0.7970   |
| 0.0423        | 45.0  | 6750 | 1.6710          | 0.7887   |
| 0.0086        | 46.0  | 6900 | 1.6167          | 0.7937   |
| 0.0455        | 47.0  | 7050 | 1.6337          | 0.7937   |
| 0.0453        | 48.0  | 7200 | 1.6348          | 0.7937   |
| 0.0064        | 49.0  | 7350 | 1.5986          | 0.7953   |
| 0.0088        | 50.0  | 7500 | 1.5974          | 0.7970   |


### 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_Adamax_lr001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7970049916805324, "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