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# SMIDS_1x_beit_large_Adamax_lr00001_fold2

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: 0.7202
- Accuracy: 0.9052

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2581        | 1.0   | 150  | 0.2638          | 0.9035   |
| 0.2098        | 2.0   | 300  | 0.3064          | 0.8835   |
| 0.1037        | 3.0   | 450  | 0.3149          | 0.8968   |
| 0.1318        | 4.0   | 600  | 0.3624          | 0.9002   |
| 0.0765        | 5.0   | 750  | 0.3794          | 0.9151   |
| 0.0836        | 6.0   | 900  | 0.4082          | 0.9085   |
| 0.0105        | 7.0   | 1050 | 0.4844          | 0.9068   |
| 0.0013        | 8.0   | 1200 | 0.5208          | 0.9085   |
| 0.0003        | 9.0   | 1350 | 0.4795          | 0.9185   |
| 0.0007        | 10.0  | 1500 | 0.5459          | 0.9168   |
| 0.0002        | 11.0  | 1650 | 0.5732          | 0.9118   |
| 0.0704        | 12.0  | 1800 | 0.6154          | 0.9035   |
| 0.0013        | 13.0  | 1950 | 0.5877          | 0.9151   |
| 0.0457        | 14.0  | 2100 | 0.6021          | 0.9151   |
| 0.0002        | 15.0  | 2250 | 0.6066          | 0.9168   |
| 0.0056        | 16.0  | 2400 | 0.6173          | 0.9101   |
| 0.0074        | 17.0  | 2550 | 0.6166          | 0.9135   |
| 0.0           | 18.0  | 2700 | 0.6448          | 0.9135   |
| 0.0285        | 19.0  | 2850 | 0.6278          | 0.9068   |
| 0.0213        | 20.0  | 3000 | 0.6309          | 0.9068   |
| 0.0044        | 21.0  | 3150 | 0.6358          | 0.9068   |
| 0.0031        | 22.0  | 3300 | 0.6683          | 0.9035   |
| 0.0001        | 23.0  | 3450 | 0.6531          | 0.9035   |
| 0.0147        | 24.0  | 3600 | 0.6466          | 0.9151   |
| 0.0284        | 25.0  | 3750 | 0.6523          | 0.9118   |
| 0.0097        | 26.0  | 3900 | 0.6484          | 0.9085   |
| 0.0006        | 27.0  | 4050 | 0.6464          | 0.9135   |
| 0.014         | 28.0  | 4200 | 0.6382          | 0.9118   |
| 0.0004        | 29.0  | 4350 | 0.6558          | 0.9118   |
| 0.0001        | 30.0  | 4500 | 0.6496          | 0.9135   |
| 0.0           | 31.0  | 4650 | 0.6886          | 0.9068   |
| 0.0002        | 32.0  | 4800 | 0.7055          | 0.9085   |
| 0.0001        | 33.0  | 4950 | 0.6813          | 0.9085   |
| 0.0001        | 34.0  | 5100 | 0.6992          | 0.9018   |
| 0.0           | 35.0  | 5250 | 0.7021          | 0.9052   |
| 0.0           | 36.0  | 5400 | 0.7190          | 0.9035   |
| 0.0           | 37.0  | 5550 | 0.7083          | 0.9068   |
| 0.0           | 38.0  | 5700 | 0.7098          | 0.9085   |
| 0.0           | 39.0  | 5850 | 0.7256          | 0.9035   |
| 0.0           | 40.0  | 6000 | 0.6873          | 0.9101   |
| 0.0           | 41.0  | 6150 | 0.6825          | 0.9068   |
| 0.0156        | 42.0  | 6300 | 0.6883          | 0.9101   |
| 0.0           | 43.0  | 6450 | 0.7127          | 0.9068   |
| 0.0           | 44.0  | 6600 | 0.7172          | 0.9085   |
| 0.0           | 45.0  | 6750 | 0.7130          | 0.9068   |
| 0.0           | 46.0  | 6900 | 0.7141          | 0.9035   |
| 0.0           | 47.0  | 7050 | 0.7201          | 0.9052   |
| 0.0           | 48.0  | 7200 | 0.7172          | 0.9068   |
| 0.0           | 49.0  | 7350 | 0.7196          | 0.9052   |
| 0.0           | 50.0  | 7500 | 0.7202          | 0.9052   |


### 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_lr00001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9051580698835274, "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