---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut_marriage_RT_539-135_301123
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# donut_marriage_RT_539-135_301123

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: 0.1088

## 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1504        | 1.0   | 270  | 0.5023          |
| 0.1444        | 2.0   | 540  | 0.2738          |
| 0.2701        | 3.0   | 810  | 0.1902          |
| 0.3624        | 4.0   | 1080 | 0.1666          |
| 0.1274        | 5.0   | 1350 | 0.1542          |
| 0.0369        | 6.0   | 1620 | 0.1537          |
| 0.0615        | 7.0   | 1890 | 0.1402          |
| 0.0271        | 8.0   | 2160 | 0.1293          |
| 0.0142        | 9.0   | 2430 | 0.1262          |
| 0.2481        | 10.0  | 2700 | 0.1255          |
| 0.002         | 11.0  | 2970 | 0.1260          |
| 0.0098        | 12.0  | 3240 | 0.1244          |
| 0.0045        | 13.0  | 3510 | 0.1214          |
| 0.0001        | 14.0  | 3780 | 0.1278          |
| 0.0011        | 15.0  | 4050 | 0.1227          |
| 0.0006        | 16.0  | 4320 | 0.1226          |
| 0.0003        | 17.0  | 4590 | 0.1212          |
| 0.0022        | 18.0  | 4860 | 0.1170          |
| 0.0002        | 19.0  | 5130 | 0.1141          |
| 0.0002        | 20.0  | 5400 | 0.1176          |
| 0.0004        | 21.0  | 5670 | 0.1142          |
| 0.0001        | 22.0  | 5940 | 0.1096          |
| 0.0003        | 23.0  | 6210 | 0.1090          |
| 0.0002        | 24.0  | 6480 | 0.1092          |
| 0.0001        | 25.0  | 6750 | 0.1088          |


### Framework versions

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