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# SMIDS_1x_beit_large_Adamax_lr001_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: 1.6470
- Accuracy: 0.8217

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8956        | 1.0   | 150  | 0.8250          | 0.5933   |
| 0.7783        | 2.0   | 300  | 0.7100          | 0.635    |
| 0.633         | 3.0   | 450  | 0.6071          | 0.7317   |
| 0.6452        | 4.0   | 600  | 0.5767          | 0.75     |
| 0.6563        | 5.0   | 750  | 0.5442          | 0.7617   |
| 0.4989        | 6.0   | 900  | 0.6272          | 0.7233   |
| 0.4692        | 7.0   | 1050 | 0.5228          | 0.7983   |
| 0.4795        | 8.0   | 1200 | 0.5594          | 0.78     |
| 0.4489        | 9.0   | 1350 | 0.6009          | 0.7667   |
| 0.4597        | 10.0  | 1500 | 0.4966          | 0.7983   |
| 0.3974        | 11.0  | 1650 | 0.5435          | 0.795    |
| 0.2877        | 12.0  | 1800 | 0.5855          | 0.795    |
| 0.3456        | 13.0  | 1950 | 0.5116          | 0.7967   |
| 0.233         | 14.0  | 2100 | 0.5855          | 0.8017   |
| 0.2728        | 15.0  | 2250 | 0.6147          | 0.8117   |
| 0.2942        | 16.0  | 2400 | 0.7146          | 0.795    |
| 0.2344        | 17.0  | 2550 | 0.7543          | 0.7767   |
| 0.1914        | 18.0  | 2700 | 0.8148          | 0.79     |
| 0.2483        | 19.0  | 2850 | 0.7052          | 0.8117   |
| 0.1137        | 20.0  | 3000 | 1.0041          | 0.8133   |
| 0.2738        | 21.0  | 3150 | 0.9710          | 0.7917   |
| 0.1952        | 22.0  | 3300 | 0.7192          | 0.8033   |
| 0.0779        | 23.0  | 3450 | 1.0125          | 0.8167   |
| 0.0546        | 24.0  | 3600 | 1.4664          | 0.8      |
| 0.0865        | 25.0  | 3750 | 1.3684          | 0.81     |
| 0.0689        | 26.0  | 3900 | 1.3563          | 0.8133   |
| 0.0152        | 27.0  | 4050 | 1.4257          | 0.8167   |
| 0.057         | 28.0  | 4200 | 1.5114          | 0.8167   |
| 0.0073        | 29.0  | 4350 | 1.5841          | 0.825    |
| 0.0003        | 30.0  | 4500 | 1.4971          | 0.8217   |
| 0.027         | 31.0  | 4650 | 1.5944          | 0.8267   |
| 0.0586        | 32.0  | 4800 | 1.5845          | 0.8133   |
| 0.0951        | 33.0  | 4950 | 1.4127          | 0.8167   |
| 0.0392        | 34.0  | 5100 | 1.6891          | 0.8183   |
| 0.0034        | 35.0  | 5250 | 1.7127          | 0.8183   |
| 0.0006        | 36.0  | 5400 | 1.3845          | 0.8283   |
| 0.0507        | 37.0  | 5550 | 1.6114          | 0.8217   |
| 0.0228        | 38.0  | 5700 | 1.6596          | 0.8083   |
| 0.0789        | 39.0  | 5850 | 1.6447          | 0.8083   |
| 0.0435        | 40.0  | 6000 | 1.5707          | 0.8217   |
| 0.0006        | 41.0  | 6150 | 1.5678          | 0.8233   |
| 0.0159        | 42.0  | 6300 | 1.5537          | 0.8167   |
| 0.0362        | 43.0  | 6450 | 1.4587          | 0.8217   |
| 0.0098        | 44.0  | 6600 | 1.4929          | 0.8183   |
| 0.0001        | 45.0  | 6750 | 1.5249          | 0.82     |
| 0.0           | 46.0  | 6900 | 1.5729          | 0.8167   |
| 0.0144        | 47.0  | 7050 | 1.5981          | 0.815    |
| 0.0           | 48.0  | 7200 | 1.6209          | 0.8133   |
| 0.0           | 49.0  | 7350 | 1.6394          | 0.8167   |
| 0.0001        | 50.0  | 7500 | 1.6470          | 0.8217   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8216666666666667, "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