---
license: mit
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut_pdf_ocr
  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_pdf_ocr

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: 0.0821

## 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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6648        | 1.0   | 47   | 0.2550          |
| 0.3772        | 2.0   | 94   | 0.0895          |
| 0.1732        | 3.0   | 141  | 0.0862          |
| 0.1244        | 4.0   | 188  | 0.0718          |
| 0.0867        | 5.0   | 235  | 0.0473          |
| 0.1035        | 6.0   | 282  | 0.0640          |
| 0.1703        | 7.0   | 329  | 0.0877          |
| 0.0324        | 8.0   | 376  | 0.0722          |
| 0.033         | 9.0   | 423  | 0.0701          |
| 0.0404        | 10.0  | 470  | 0.0627          |
| 0.0198        | 11.0  | 517  | 0.0770          |
| 0.007         | 12.0  | 564  | 0.0730          |
| 0.0207        | 13.0  | 611  | 0.0885          |
| 0.0528        | 14.0  | 658  | 0.0898          |
| 0.0189        | 15.0  | 705  | 0.0588          |
| 0.0977        | 16.0  | 752  | 0.0563          |
| 0.0542        | 17.0  | 799  | 0.0647          |
| 0.0114        | 18.0  | 846  | 0.0674          |
| 0.0056        | 19.0  | 893  | 0.0726          |
| 0.005         | 20.0  | 940  | 0.0797          |
| 0.0005        | 21.0  | 987  | 0.0704          |
| 0.0023        | 22.0  | 1034 | 0.0864          |
| 0.0105        | 23.0  | 1081 | 0.0830          |
| 0.0014        | 24.0  | 1128 | 0.0806          |
| 0.0006        | 25.0  | 1175 | 0.0826          |
| 0.0012        | 26.0  | 1222 | 0.0790          |
| 0.0006        | 27.0  | 1269 | 0.0751          |
| 0.0022        | 28.0  | 1316 | 0.0786          |
| 0.0075        | 29.0  | 1363 | 0.0816          |
| 0.0024        | 30.0  | 1410 | 0.0821          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3