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# smids_1x_beit_base_adamax_001_fold5

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1833
- Accuracy: 0.7633

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9804        | 1.0   | 75   | 0.8561          | 0.5383   |
| 0.8823        | 2.0   | 150  | 0.7905          | 0.5767   |
| 0.8002        | 3.0   | 225  | 0.7961          | 0.5633   |
| 0.8142        | 4.0   | 300  | 0.8679          | 0.6133   |
| 0.6765        | 5.0   | 375  | 0.6964          | 0.6817   |
| 0.652         | 6.0   | 450  | 0.6686          | 0.7      |
| 0.6785        | 7.0   | 525  | 0.6625          | 0.7067   |
| 0.5659        | 8.0   | 600  | 0.6154          | 0.7217   |
| 0.6383        | 9.0   | 675  | 0.6262          | 0.7117   |
| 0.5991        | 10.0  | 750  | 0.5856          | 0.7633   |
| 0.4627        | 11.0  | 825  | 0.5901          | 0.7633   |
| 0.5021        | 12.0  | 900  | 0.5968          | 0.7433   |
| 0.5421        | 13.0  | 975  | 0.5857          | 0.74     |
| 0.3951        | 14.0  | 1050 | 0.5723          | 0.7733   |
| 0.4943        | 15.0  | 1125 | 0.6046          | 0.7533   |
| 0.4076        | 16.0  | 1200 | 0.6196          | 0.7567   |
| 0.379         | 17.0  | 1275 | 0.5906          | 0.7817   |
| 0.3759        | 18.0  | 1350 | 0.5998          | 0.775    |
| 0.3383        | 19.0  | 1425 | 0.6508          | 0.7567   |
| 0.2622        | 20.0  | 1500 | 0.6675          | 0.775    |
| 0.316         | 21.0  | 1575 | 0.7118          | 0.785    |
| 0.2478        | 22.0  | 1650 | 0.7508          | 0.78     |
| 0.2696        | 23.0  | 1725 | 0.7052          | 0.7733   |
| 0.1441        | 24.0  | 1800 | 0.8658          | 0.7783   |
| 0.1966        | 25.0  | 1875 | 0.9393          | 0.7417   |
| 0.1228        | 26.0  | 1950 | 1.0783          | 0.7567   |
| 0.2151        | 27.0  | 2025 | 1.0051          | 0.7533   |
| 0.1799        | 28.0  | 2100 | 1.0898          | 0.755    |
| 0.1053        | 29.0  | 2175 | 1.0567          | 0.7533   |
| 0.122         | 30.0  | 2250 | 1.1544          | 0.7583   |
| 0.1375        | 31.0  | 2325 | 1.3014          | 0.7617   |
| 0.0659        | 32.0  | 2400 | 1.6359          | 0.765    |
| 0.0997        | 33.0  | 2475 | 1.4213          | 0.7717   |
| 0.0852        | 34.0  | 2550 | 1.6657          | 0.7467   |
| 0.0752        | 35.0  | 2625 | 1.5943          | 0.7733   |
| 0.0405        | 36.0  | 2700 | 1.5865          | 0.7583   |
| 0.0174        | 37.0  | 2775 | 1.8002          | 0.7533   |
| 0.0364        | 38.0  | 2850 | 1.6078          | 0.7583   |
| 0.0269        | 39.0  | 2925 | 2.0543          | 0.7667   |
| 0.0034        | 40.0  | 3000 | 2.1698          | 0.7517   |
| 0.0428        | 41.0  | 3075 | 1.8011          | 0.74     |
| 0.0355        | 42.0  | 3150 | 2.1588          | 0.7567   |
| 0.0068        | 43.0  | 3225 | 2.0789          | 0.7617   |
| 0.013         | 44.0  | 3300 | 2.0235          | 0.76     |
| 0.0102        | 45.0  | 3375 | 1.9567          | 0.7567   |
| 0.0216        | 46.0  | 3450 | 1.9788          | 0.765    |
| 0.0016        | 47.0  | 3525 | 2.1056          | 0.765    |
| 0.0046        | 48.0  | 3600 | 2.1156          | 0.7633   |
| 0.0115        | 49.0  | 3675 | 2.2014          | 0.7617   |
| 0.0156        | 50.0  | 3750 | 2.1833          | 0.7633   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "smids_1x_beit_base_adamax_001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7633333333333333, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us