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# donut_marriage_RT_001

This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3953

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0315        | 1.0   | 163  | 0.9688          |
| 0.5694        | 2.0   | 326  | 0.5084          |
| 0.5065        | 3.0   | 489  | 0.4196          |
| 0.1008        | 4.0   | 652  | 0.3998          |
| 0.1531        | 5.0   | 815  | 0.3687          |
| 0.1606        | 6.0   | 978  | 0.3642          |
| 0.1383        | 7.0   | 1141 | 0.3745          |
| 0.0956        | 8.0   | 1304 | 0.3856          |
| 0.0331        | 9.0   | 1467 | 0.3850          |
| 0.0032        | 10.0  | 1630 | 0.3920          |
| 0.0164        | 11.0  | 1793 | 0.3953          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "base_model": "naver-clova-ix/donut-base", "model-index": [{"name": "donut_marriage_RT_001", "results": []}]}
transformers tensorboard safetensors vision-encoder-decoder generated_from_trainer dataset:imagefolder base_model:naver-clova-ix/donut-base license:mit endpoints_compatible region:us