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# SMIDS_1x_beit_large_Adamax_lr001_fold1

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: 2.0003
- Accuracy: 0.7896

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8351        | 1.0   | 151  | 1.0795          | 0.5008   |
| 0.7631        | 2.0   | 302  | 0.7812          | 0.5960   |
| 0.8426        | 3.0   | 453  | 0.7772          | 0.6477   |
| 0.7292        | 4.0   | 604  | 0.8080          | 0.6194   |
| 0.7555        | 5.0   | 755  | 0.7254          | 0.6661   |
| 0.691         | 6.0   | 906  | 0.7665          | 0.6027   |
| 0.6236        | 7.0   | 1057 | 0.7740          | 0.6678   |
| 0.6332        | 8.0   | 1208 | 0.6618          | 0.6978   |
| 0.6368        | 9.0   | 1359 | 0.9153          | 0.6377   |
| 0.5288        | 10.0  | 1510 | 0.7121          | 0.6811   |
| 0.5737        | 11.0  | 1661 | 0.6639          | 0.6845   |
| 0.5581        | 12.0  | 1812 | 0.5949          | 0.7446   |
| 0.556         | 13.0  | 1963 | 0.6000          | 0.7462   |
| 0.4673        | 14.0  | 2114 | 0.5871          | 0.7412   |
| 0.3652        | 15.0  | 2265 | 0.6755          | 0.7412   |
| 0.4031        | 16.0  | 2416 | 0.6106          | 0.7529   |
| 0.4101        | 17.0  | 2567 | 0.6485          | 0.7179   |
| 0.3518        | 18.0  | 2718 | 0.6202          | 0.7346   |
| 0.3332        | 19.0  | 2869 | 0.6340          | 0.7663   |
| 0.2538        | 20.0  | 3020 | 0.6566          | 0.7446   |
| 0.4113        | 21.0  | 3171 | 0.6417          | 0.7362   |
| 0.3869        | 22.0  | 3322 | 0.6709          | 0.7496   |
| 0.2362        | 23.0  | 3473 | 0.7535          | 0.7830   |
| 0.1663        | 24.0  | 3624 | 0.8058          | 0.7563   |
| 0.2778        | 25.0  | 3775 | 0.8846          | 0.7312   |
| 0.2637        | 26.0  | 3926 | 0.9788          | 0.7579   |
| 0.1505        | 27.0  | 4077 | 1.2650          | 0.7513   |
| 0.2315        | 28.0  | 4228 | 0.9468          | 0.7613   |
| 0.1938        | 29.0  | 4379 | 1.0400          | 0.7796   |
| 0.0736        | 30.0  | 4530 | 1.4195          | 0.7746   |
| 0.0736        | 31.0  | 4681 | 1.1073          | 0.7963   |
| 0.1157        | 32.0  | 4832 | 1.2786          | 0.7813   |
| 0.1143        | 33.0  | 4983 | 1.5616          | 0.7763   |
| 0.0586        | 34.0  | 5134 | 1.6606          | 0.7763   |
| 0.0553        | 35.0  | 5285 | 1.4974          | 0.7813   |
| 0.0336        | 36.0  | 5436 | 1.7100          | 0.7679   |
| 0.0469        | 37.0  | 5587 | 1.6424          | 0.7646   |
| 0.0372        | 38.0  | 5738 | 1.8662          | 0.7579   |
| 0.0553        | 39.0  | 5889 | 1.7586          | 0.7546   |
| 0.0221        | 40.0  | 6040 | 1.7591          | 0.7763   |
| 0.0015        | 41.0  | 6191 | 1.5651          | 0.7763   |
| 0.0064        | 42.0  | 6342 | 1.7590          | 0.7947   |
| 0.0429        | 43.0  | 6493 | 1.8412          | 0.7780   |
| 0.0117        | 44.0  | 6644 | 1.9309          | 0.7880   |
| 0.0005        | 45.0  | 6795 | 1.9420          | 0.7930   |
| 0.0004        | 46.0  | 6946 | 1.9816          | 0.7846   |
| 0.0574        | 47.0  | 7097 | 1.9767          | 0.7880   |
| 0.0412        | 48.0  | 7248 | 2.0632          | 0.7863   |
| 0.0341        | 49.0  | 7399 | 2.0013          | 0.7863   |
| 0.0002        | 50.0  | 7550 | 2.0003          | 0.7896   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7896494156928213, "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