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# beit-base-patch16-224

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8528
- Accuracy: 0.8268
- Precision: 0.8303
- Recall: 0.8268
- F1 Score: 0.8283

## 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: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 45

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| No log        | 0.8   | 2    | 0.6993          | 0.5882   | 0.5390    | 0.5882 | 0.5541   |
| No log        | 2.0   | 5    | 0.5971          | 0.6863   | 0.6806    | 0.6863 | 0.6033   |
| No log        | 2.8   | 7    | 0.5306          | 0.8039   | 0.8000    | 0.8039 | 0.8006   |
| No log        | 4.0   | 10   | 0.4828          | 0.7255   | 0.7229    | 0.7255 | 0.6859   |
| No log        | 4.8   | 12   | 0.3812          | 0.7843   | 0.7786    | 0.7843 | 0.7784   |
| 0.5413        | 6.0   | 15   | 0.5268          | 0.7451   | 0.7461    | 0.7451 | 0.7141   |
| 0.5413        | 6.8   | 17   | 0.5349          | 0.7451   | 0.8556    | 0.7451 | 0.7502   |
| 0.5413        | 8.0   | 20   | 0.4120          | 0.8039   | 0.8485    | 0.8039 | 0.7756   |
| 0.5413        | 8.8   | 22   | 0.3156          | 0.8039   | 0.8003    | 0.8039 | 0.7963   |
| 0.5413        | 10.0  | 25   | 0.3217          | 0.8039   | 0.8061    | 0.8039 | 0.7909   |
| 0.5413        | 10.8  | 27   | 0.5161          | 0.7843   | 0.7870    | 0.7843 | 0.7664   |
| 0.0919        | 12.0  | 30   | 0.3677          | 0.8431   | 0.8498    | 0.8431 | 0.8451   |
| 0.0919        | 12.8  | 32   | 0.4631          | 0.8431   | 0.8407    | 0.8431 | 0.8405   |
| 0.0919        | 14.0  | 35   | 0.5001          | 0.8235   | 0.8214    | 0.8235 | 0.8221   |
| 0.0919        | 14.8  | 37   | 0.4489          | 0.8431   | 0.8431    | 0.8431 | 0.8431   |
| 0.0919        | 16.0  | 40   | 0.5892          | 0.7843   | 0.7799    | 0.7843 | 0.7731   |
| 0.0919        | 16.8  | 42   | 0.6579          | 0.7843   | 0.7799    | 0.7843 | 0.7731   |
| 0.006         | 18.0  | 45   | 0.7038          | 0.7843   | 0.7799    | 0.7843 | 0.7731   |
| 0.006         | 18.8  | 47   | 0.5864          | 0.8627   | 0.8737    | 0.8627 | 0.8651   |
| 0.006         | 20.0  | 50   | 0.5488          | 0.8627   | 0.8737    | 0.8627 | 0.8651   |
| 0.006         | 20.8  | 52   | 0.6651          | 0.8039   | 0.8003    | 0.8039 | 0.7963   |
| 0.006         | 22.0  | 55   | 0.6265          | 0.8039   | 0.8000    | 0.8039 | 0.8006   |
| 0.006         | 22.8  | 57   | 0.5229          | 0.8627   | 0.8653    | 0.8627 | 0.8637   |
| 0.0048        | 24.0  | 60   | 0.5421          | 0.8627   | 0.8653    | 0.8627 | 0.8637   |
| 0.0048        | 24.8  | 62   | 0.6335          | 0.8235   | 0.8205    | 0.8235 | 0.8187   |
| 0.0048        | 26.0  | 65   | 1.0379          | 0.8039   | 0.8201    | 0.8039 | 0.7841   |
| 0.0048        | 26.8  | 67   | 0.9758          | 0.8235   | 0.8366    | 0.8235 | 0.8089   |
| 0.0048        | 28.0  | 70   | 0.6117          | 0.8235   | 0.8205    | 0.8235 | 0.8187   |
| 0.0048        | 28.8  | 72   | 0.5403          | 0.8627   | 0.8613    | 0.8627 | 0.8617   |
| 0.0063        | 30.0  | 75   | 0.6469          | 0.8431   | 0.8407    | 0.8431 | 0.8405   |
| 0.0063        | 30.8  | 77   | 0.7014          | 0.8235   | 0.8205    | 0.8235 | 0.8187   |
| 0.0063        | 32.0  | 80   | 0.7514          | 0.8235   | 0.8205    | 0.8235 | 0.8187   |
| 0.0063        | 32.8  | 82   | 0.7771          | 0.8235   | 0.8248    | 0.8235 | 0.8144   |
| 0.0063        | 34.0  | 85   | 0.7599          | 0.8039   | 0.8003    | 0.8039 | 0.7963   |
| 0.0063        | 34.8  | 87   | 0.7554          | 0.8039   | 0.8003    | 0.8039 | 0.7963   |
| 0.0045        | 36.0  | 90   | 0.7308          | 0.8039   | 0.8003    | 0.8039 | 0.7963   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1

absent present