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# WS800_BEiT_42820085

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: 0.0451
- Accuracy: 1.0

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.96  | 6    | 0.6592          | 0.85     |
| No log        | 1.92  | 12   | 0.4828          | 0.9875   |
| No log        | 2.88  | 18   | 0.3227          | 0.9875   |
| No log        | 4.0   | 25   | 0.2001          | 0.9875   |
| No log        | 4.96  | 31   | 0.1378          | 0.9875   |
| No log        | 5.92  | 37   | 0.0838          | 1.0      |
| No log        | 6.88  | 43   | 0.0635          | 1.0      |
| 0.297         | 8.0   | 50   | 0.0510          | 1.0      |
| 0.297         | 8.96  | 56   | 0.0462          | 1.0      |
| 0.297         | 9.6   | 60   | 0.0451          | 1.0      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0

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