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# SMIDS_5x_beit_large_Adamax_lr00001_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: 0.7867
- Accuracy: 0.9182

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2514        | 1.0   | 751   | 0.2493          | 0.9082   |
| 0.0398        | 2.0   | 1502  | 0.3266          | 0.9015   |
| 0.0407        | 3.0   | 2253  | 0.4501          | 0.9098   |
| 0.0125        | 4.0   | 3004  | 0.5176          | 0.9065   |
| 0.0193        | 5.0   | 3755  | 0.5701          | 0.9065   |
| 0.0005        | 6.0   | 4506  | 0.7082          | 0.8982   |
| 0.009         | 7.0   | 5257  | 0.6463          | 0.9015   |
| 0.0041        | 8.0   | 6008  | 0.7694          | 0.9048   |
| 0.0           | 9.0   | 6759  | 0.7657          | 0.9065   |
| 0.0003        | 10.0  | 7510  | 0.6687          | 0.9132   |
| 0.0008        | 11.0  | 8261  | 0.7182          | 0.9065   |
| 0.0           | 12.0  | 9012  | 0.7402          | 0.9082   |
| 0.0           | 13.0  | 9763  | 0.7624          | 0.9065   |
| 0.0           | 14.0  | 10514 | 0.7472          | 0.9215   |
| 0.0004        | 15.0  | 11265 | 0.7655          | 0.9048   |
| 0.0006        | 16.0  | 12016 | 0.7144          | 0.9132   |
| 0.0004        | 17.0  | 12767 | 0.7444          | 0.9115   |
| 0.0           | 18.0  | 13518 | 0.8105          | 0.9032   |
| 0.0           | 19.0  | 14269 | 0.8002          | 0.9132   |
| 0.004         | 20.0  | 15020 | 0.7526          | 0.9165   |
| 0.0099        | 21.0  | 15771 | 0.7890          | 0.9082   |
| 0.0166        | 22.0  | 16522 | 0.8407          | 0.9048   |
| 0.0001        | 23.0  | 17273 | 0.8243          | 0.9065   |
| 0.0           | 24.0  | 18024 | 0.8363          | 0.9082   |
| 0.0           | 25.0  | 18775 | 0.7737          | 0.9149   |
| 0.0           | 26.0  | 19526 | 0.8098          | 0.9032   |
| 0.0           | 27.0  | 20277 | 0.7977          | 0.9165   |
| 0.0           | 28.0  | 21028 | 0.7750          | 0.9048   |
| 0.0           | 29.0  | 21779 | 0.8662          | 0.9048   |
| 0.0           | 30.0  | 22530 | 0.8271          | 0.9065   |
| 0.0           | 31.0  | 23281 | 0.8091          | 0.9065   |
| 0.042         | 32.0  | 24032 | 0.8109          | 0.9032   |
| 0.0016        | 33.0  | 24783 | 0.7857          | 0.9065   |
| 0.0           | 34.0  | 25534 | 0.8163          | 0.9032   |
| 0.0001        | 35.0  | 26285 | 0.7805          | 0.9115   |
| 0.0007        | 36.0  | 27036 | 0.8099          | 0.9048   |
| 0.0           | 37.0  | 27787 | 0.7888          | 0.9115   |
| 0.0           | 38.0  | 28538 | 0.8019          | 0.9132   |
| 0.0           | 39.0  | 29289 | 0.8257          | 0.9048   |
| 0.0           | 40.0  | 30040 | 0.7918          | 0.9065   |
| 0.0           | 41.0  | 30791 | 0.8392          | 0.9065   |
| 0.0           | 42.0  | 31542 | 0.7829          | 0.9098   |
| 0.0           | 43.0  | 32293 | 0.7659          | 0.9132   |
| 0.0           | 44.0  | 33044 | 0.8018          | 0.9132   |
| 0.0           | 45.0  | 33795 | 0.7895          | 0.9149   |
| 0.0           | 46.0  | 34546 | 0.7797          | 0.9098   |
| 0.0           | 47.0  | 35297 | 0.7885          | 0.9149   |
| 0.0           | 48.0  | 36048 | 0.7887          | 0.9165   |
| 0.0           | 49.0  | 36799 | 0.7847          | 0.9165   |
| 0.0           | 50.0  | 37550 | 0.7867          | 0.9182   |


### 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_5x_beit_large_Adamax_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": 0.9181969949916527, "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