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# SMIDS_10x_beit_base_sgd_lr00001_fold1

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: 0.8274
- Accuracy: 0.6411

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1827        | 1.0   | 751   | 1.1967          | 0.3940   |
| 1.1441        | 2.0   | 1502  | 1.1684          | 0.4007   |
| 1.1144        | 3.0   | 2253  | 1.1432          | 0.4090   |
| 1.0939        | 4.0   | 3004  | 1.1210          | 0.4224   |
| 1.045         | 5.0   | 3755  | 1.1003          | 0.4307   |
| 1.0432        | 6.0   | 4506  | 1.0811          | 0.4508   |
| 1.0436        | 7.0   | 5257  | 1.0628          | 0.4641   |
| 0.9771        | 8.0   | 6008  | 1.0458          | 0.4725   |
| 0.9844        | 9.0   | 6759  | 1.0301          | 0.4942   |
| 0.945         | 10.0  | 7510  | 1.0152          | 0.5058   |
| 0.9762        | 11.0  | 8261  | 1.0014          | 0.5225   |
| 0.9493        | 12.0  | 9012  | 0.9884          | 0.5292   |
| 0.9554        | 13.0  | 9763  | 0.9758          | 0.5359   |
| 0.9422        | 14.0  | 10514 | 0.9643          | 0.5526   |
| 0.9174        | 15.0  | 11265 | 0.9535          | 0.5693   |
| 0.938         | 16.0  | 12016 | 0.9430          | 0.5826   |
| 0.9008        | 17.0  | 12767 | 0.9331          | 0.5993   |
| 0.8964        | 18.0  | 13518 | 0.9240          | 0.6060   |
| 0.8914        | 19.0  | 14269 | 0.9156          | 0.6027   |
| 0.9121        | 20.0  | 15020 | 0.9078          | 0.6110   |
| 0.85          | 21.0  | 15771 | 0.9006          | 0.6127   |
| 0.8351        | 22.0  | 16522 | 0.8938          | 0.6144   |
| 0.8562        | 23.0  | 17273 | 0.8876          | 0.6127   |
| 0.8579        | 24.0  | 18024 | 0.8819          | 0.6127   |
| 0.8392        | 25.0  | 18775 | 0.8765          | 0.6194   |
| 0.884         | 26.0  | 19526 | 0.8716          | 0.6277   |
| 0.8305        | 27.0  | 20277 | 0.8672          | 0.6294   |
| 0.8444        | 28.0  | 21028 | 0.8629          | 0.6294   |
| 0.8309        | 29.0  | 21779 | 0.8592          | 0.6361   |
| 0.8043        | 30.0  | 22530 | 0.8557          | 0.6394   |
| 0.8327        | 31.0  | 23281 | 0.8527          | 0.6411   |
| 0.7831        | 32.0  | 24032 | 0.8497          | 0.6377   |
| 0.805         | 33.0  | 24783 | 0.8469          | 0.6377   |
| 0.761         | 34.0  | 25534 | 0.8444          | 0.6344   |
| 0.7653        | 35.0  | 26285 | 0.8420          | 0.6327   |
| 0.8036        | 36.0  | 27036 | 0.8399          | 0.6344   |
| 0.8145        | 37.0  | 27787 | 0.8381          | 0.6344   |
| 0.7958        | 38.0  | 28538 | 0.8364          | 0.6361   |
| 0.8039        | 39.0  | 29289 | 0.8348          | 0.6344   |
| 0.7963        | 40.0  | 30040 | 0.8335          | 0.6361   |
| 0.7902        | 41.0  | 30791 | 0.8322          | 0.6394   |
| 0.7553        | 42.0  | 31542 | 0.8310          | 0.6411   |
| 0.8144        | 43.0  | 32293 | 0.8301          | 0.6411   |
| 0.8002        | 44.0  | 33044 | 0.8293          | 0.6411   |
| 0.8328        | 45.0  | 33795 | 0.8287          | 0.6411   |
| 0.7812        | 46.0  | 34546 | 0.8282          | 0.6411   |
| 0.7871        | 47.0  | 35297 | 0.8278          | 0.6411   |
| 0.7447        | 48.0  | 36048 | 0.8275          | 0.6411   |
| 0.798         | 49.0  | 36799 | 0.8274          | 0.6411   |
| 0.7782        | 50.0  | 37550 | 0.8274          | 0.6411   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "SMIDS_10x_beit_base_sgd_lr00001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6410684474123539, "name": "Accuracy"}]}]}]}
transformers 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